biometric time series: Topics by WorldWideScience.org

Sample records for biometric time series

Multi-complexity ensemble measures for gait time series analysis: application to diagnostics, monitoring and biometrics.

Science.gov (United States)

Gavrishchaka, Valeriy; Senyukova, Olga; Davis, Kristina

2015-01-01

Previously, we have proposed to use complementary complexity measures discovered by boosting-like ensemble learning for the enhancement of quantitative indicators dealing with necessarily short physiological time series. We have confirmed robustness of such multi-complexity measures for heart rate variability analysis with the emphasis on detection of emerging and intermittent cardiac abnormalities. Recently, we presented preliminary results suggesting that such ensemble-based approach could be also effective in discovering universal meta-indicators for early detection and convenient monitoring of neurological abnormalities using gait time series. Here, we argue and demonstrate that these multi-complexity ensemble measures for gait time series analysis could have significantly wider application scope ranging from diagnostics and early detection of physiological regime change to gait-based biometrics applications.
eBiometrics: an enhanced multi-biometrics authentication technique for real-time remote applications on mobile devices

Science.gov (United States)

Kuseler, Torben; Lami, Ihsan; Jassim, Sabah; Sellahewa, Harin

2010-04-01

The use of mobile communication devices with advance sensors is growing rapidly. These sensors are enabling functions such as Image capture, Location applications, and Biometric authentication such as Fingerprint verification and Face & Handwritten signature recognition. Such ubiquitous devices are essential tools in today's global economic activities enabling anywhere-anytime financial and business transactions. Cryptographic functions and biometric-based authentication can enhance the security and confidentiality of mobile transactions. Using Biometric template security techniques in real-time biometric-based authentication are key factors for successful identity verification solutions, but are venerable to determined attacks by both fraudulent software and hardware. The EU-funded SecurePhone project has designed and implemented a multimodal biometric user authentication system on a prototype mobile communication device. However, various implementations of this project have resulted in long verification times or reduced accuracy and/or security. This paper proposes to use built-in-self-test techniques to ensure no tampering has taken place on the verification process prior to performing the actual biometric authentication. These techniques utilises the user personal identification number as a seed to generate a unique signature. This signature is then used to test the integrity of the verification process. Also, this study proposes the use of a combination of biometric modalities to provide application specific authentication in a secure environment, thus achieving optimum security level with effective processing time. I.e. to ensure that the necessary authentication steps and algorithms running on the mobile device application processor can not be undermined or modified by an imposter to get unauthorized access to the secure system.
Palmprint Verification Using Time Series Method

Directory of Open Access Journals (Sweden)

A. A. Ketut Agung Cahyawan Wiranatha

2013-11-01

Full Text Available The use of biometrics as an automatic recognition system is growing rapidly in solving security problems, palmprint is one of biometric system which often used. This paper used two steps in center of mass moment method for region of interest (ROI segmentation and apply the time series method combined with block window method as feature representation. Normalized Euclidean Distance is used to measure the similarity degrees of two feature vectors of palmprint. System testing is done using 500 samples palms, with 4 samples as the reference image and the 6 samples as test images. Experiment results show that this system can achieve a high performance with success rate about 97.33% (FNMR=1.67%, FMR=1.00 %, T=0.036.
Enrollment Time as a Requirement for Biometric Hand Recognition Systems

OpenAIRE

Carvalho, João; Sá, Vítor; Tenreiro de Magalhães, Sérgio; Santos, Henrique

2015-01-01

Biometric systems are increasingly being used as a means for authentication to provide system security in modern technologies. The performance of a biometric system depends on the accuracy, the processing speed, the template size, and the time necessary for enrollment. While much research has focused on the first three factors, enrollment time has not received as much attention. In this work, we present the findings of our research focused upon studying user’s behavior when enrolling in...
Using Hierarchical Time Series Clustering Algorithm and Wavelet Classifier for Biometric Voice Classification

Directory of Open Access Journals (Sweden)

Simon Fong

2012-01-01

Full Text Available Voice biometrics has a long history in biosecurity applications such as verification and identification based on characteristics of the human voice. The other application called voice classification which has its important role in grouping unlabelled voice samples, however, has not been widely studied in research. Lately voice classification is found useful in phone monitoring, classifying speakers’ gender, ethnicity and emotion states, and so forth. In this paper, a collection of computational algorithms are proposed to support voice classification; the algorithms are a combination of hierarchical clustering, dynamic time wrap transform, discrete wavelet transform, and decision tree. The proposed algorithms are relatively more transparent and interpretable than the existing ones, though many techniques such as Artificial Neural Networks, Support Vector Machine, and Hidden Markov Model (which inherently function like a black box have been applied for voice verification and voice identification. Two datasets, one that is generated synthetically and the other one empirically collected from past voice recognition experiment, are used to verify and demonstrate the effectiveness of our proposed voice classification algorithm.
Using Biometric Measurement in Real-Time as a Sympathetic System in Computer Games

Science.gov (United States)

Charij, Stephanie; Oikonomou, Andreas

2013-01-01

With the increasing potential for gaming hardware and peripherals to support biometrics, their application within the games industry for software and design should be considered. This paper assesses the ability to use a form of biometric measurement, heart rate, in real-time to improve the challenge and enjoyment of a game by catering it to…
Cancelable Biometrics - A Survey

OpenAIRE

Indira Chakravarthy; VVSSS. Balaram; B. Eswara Reddy

2011-01-01

In recent times Biometrics has emerged as a reliable, convenient and effective method of user authentication. However, with the increasing use of biometrics in several diverse applications, concerns about the privacy and security of biometric data contained in the database systems has increased. It is therefore imperative that Biometric systems instill confidence in the general public, by demonstrating that, these systems are robust, have low error rates and are tamper proof. In this context,...
Mobile biometric device (MBD) technology :

Energy Technology Data Exchange (ETDEWEB)

Aldridge, Chris D.

2013-06-01

Mobile biometric devices (MBDs) capable of both enrolling individuals in databases and performing identification checks of subjects in the field are seen as an important capability for military, law enforcement, and homeland security operations. The technology is advancing rapidly. The Department of Homeland Security Science and Technology Directorate through an Interagency Agreement with Sandia sponsored a series of pilot projects to obtain information for the first responder law enforcement community on further identification of requirements for mobile biometric device technology. Working with 62 different jurisdictions, including components of the Department of Homeland Security, Sandia delivered a series of reports on user operation of state-of-the-art mobile biometric devices. These reports included feedback information on MBD usage in both operational and exercise scenarios. The findings and conclusions of the project address both the limitations and possibilities of MBD technology to improve operations. Evidence of these possibilities can be found in the adoption of this technology by many agencies today and the cooperation of several law enforcement agencies in both participating in the pilot efforts and sharing of information about their own experiences in efforts undertaken separately.
Multichannel biomedical time series clustering via hierarchical probabilistic latent semantic analysis.

Science.gov (United States)

Wang, Jin; Sun, Xiangping; Nahavandi, Saeid; Kouzani, Abbas; Wu, Yuchuan; She, Mary

2014-11-01

Biomedical time series clustering that automatically groups a collection of time series according to their internal similarity is of importance for medical record management and inspection such as bio-signals archiving and retrieval. In this paper, a novel framework that automatically groups a set of unlabelled multichannel biomedical time series according to their internal structural similarity is proposed. Specifically, we treat a multichannel biomedical time series as a document and extract local segments from the time series as words. We extend a topic model, i.e., the Hierarchical probabilistic Latent Semantic Analysis (H-pLSA), which was originally developed for visual motion analysis to cluster a set of unlabelled multichannel time series. The H-pLSA models each channel of the multichannel time series using a local pLSA in the first layer. The topics learned in the local pLSA are then fed to a global pLSA in the second layer to discover the categories of multichannel time series. Experiments on a dataset extracted from multichannel Electrocardiography (ECG) signals demonstrate that the proposed method performs better than previous state-of-the-art approaches and is relatively robust to the variations of parameters including length of local segments and dictionary size. Although the experimental evaluation used the multichannel ECG signals in a biometric scenario, the proposed algorithm is a universal framework for multichannel biomedical time series clustering according to their structural similarity, which has many applications in biomedical time series management. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Handbook of biometric anti-spoofing trusted biometrics under spoofing attacks

CERN Document Server

Marcel, Sébastien; Li, Stan Z

2014-01-01

As the plethora of approaches to biometrics and their deployment continues to grow, so too does the need to combat the techniques used to subvert the aim of such biometric systems. Presenting the first definitive study of the subject, this Handbook of Biometric Anti-Spoofing reviews the state of the art in covert attacks against biometric systems, and in deriving countermeasures to these attacks. Across a range of common biometrics, including face, iris, fingerprint, speaker and gait, the book describes spoofing methods and examines the vulnerabilities of biometric systems to these attacks.
Multi-factor challenge/response approach for remote biometric authentication

Science.gov (United States)

Al-Assam, Hisham; Jassim, Sabah A.

2011-06-01

Although biometric authentication is perceived to be more reliable than traditional authentication schemes, it becomes vulnerable to many attacks when it comes to remote authentication over open networks and raises serious privacy concerns. This paper proposes a biometric-based challenge-response approach to be used for remote authentication between two parties A and B over open networks. In the proposed approach, a remote authenticator system B (e.g. a bank) challenges its client A who wants to authenticate his/her self to the system by sending a one-time public random challenge. The client A responds by employing the random challenge along with secret information obtained from a password and a token to produce a one-time cancellable representation of his freshly captured biometric sample. The one-time biometric representation, which is based on multi-factor, is then sent back to B for matching. Here, we argue that eavesdropping of the one-time random challenge and/or the resulting one-time biometric representation does not compromise the security of the system, and no information about the original biometric data is leaked. In addition to securing biometric templates, the proposed protocol offers a practical solution for the replay attack on biometric systems. Moreover, we propose a new scheme for generating a password-based pseudo random numbers/permutation to be used as a building block in the proposed approach. The proposed scheme is also designed to provide protection against repudiation. We illustrate the viability and effectiveness of the proposed approach by experimental results based on two biometric modalities: fingerprint and face biometrics.
A lightweight approach for biometric template protection

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Al-Assam, Hisham; Sellahewa, Harin; Jassim, Sabah

2009-05-01

Privacy and security are vital concerns for practical biometric systems. The concept of cancelable or revocable biometrics has been proposed as a solution for biometric template security. Revocable biometric means that biometric templates are no longer fixed over time and could be revoked in the same way as lost or stolen credit cards are. In this paper, we describe a novel and an efficient approach to biometric template protection that meets the revocability property. This scheme can be incorporated into any biometric verification scheme while maintaining, if not improving, the accuracy of the original biometric system. However, we shall demonstrate the result of applying such transforms on face biometric templates and compare the efficiency of our approach with that of the well-known random projection techniques. We shall also present the results of experimental work on recognition accuracy before and after applying the proposed transform on feature vectors that are generated by wavelet transforms. These results are based on experiments conducted on a number of well-known face image databases, e.g. Yale and ORL databases.
Biometric Template Security

Directory of Open Access Journals (Sweden)

Abhishek Nagar

2008-03-01

Full Text Available Biometric recognition offers a reliable solution to the problem of user authentication in identity management systems. With the widespread deployment of biometric systems in various applications, there are increasing concerns about the security and privacy of biometric technology. Public acceptance of biometrics technology will depend on the ability of system designers to demonstrate that these systems are robust, have low error rates, and are tamper proof. We present a high-level categorization of the various vulnerabilities of a biometric system and discuss countermeasures that have been proposed to address these vulnerabilities. In particular, we focus on biometric template security which is an important issue because, unlike passwords and tokens, compromised biometric templates cannot be revoked and reissued. Protecting the template is a challenging task due to intrauser variability in the acquired biometric traits. We present an overview of various biometric template protection schemes and discuss their advantages and limitations in terms of security, revocability, and impact on matching accuracy. A template protection scheme with provable security and acceptable recognition performance has thus far remained elusive. Development of such a scheme is crucial as biometric systems are beginning to proliferate into the core physical and information infrastructure of our society.
Two barriers to realizing the benefits of biometrics: a chain perspective on biometrics and identity fraud as biometrics' real challenge

Science.gov (United States)

Grijpink, Jan

2004-06-01

Along at least twelve dimensions biometric systems might vary. We need to exploit this variety to manoeuvre biometrics into place to be able to realise its social potential. Subsequently, two perspectives on biometrics are proposed revealing that biometrics will probably be ineffective in combating identity fraud, organised crime and terrorism: (1) the value chain perspective explains the first barrier: our strong preference for large scale biometric systems for general compulsory use. These biometric systems cause successful infringements to spread unnoticed. A biometric system will only function adequately if biometrics is indispensable for solving the dominant chain problem. Multi-chain use of biometrics takes it beyond the boundaries of good manageability. (2) the identity fraud perspective exposes the second barrier: our traditional approach to identity verification. We focus on identity documents, neglecting the person and the situation involved. Moreover, western legal cultures have made identity verification procedures known, transparent, uniform and predictable. Thus, we have developed a blind spot to identity fraud. Biometrics provides good potential to better checking persons, but will probably be used to enhance identity documents. Biometrics will only pay off if it confronts the identity fraudster with less predictable verification processes and more risks of his identity fraud being spotted. Standardised large scale applications of biometrics for general compulsory use without countervailing measures will probably produce the reverse. This contribution tentatively presents a few headlines for an overall biometrics strategy that could better resist identity fraud.
Biometric and Emotion Identification: An ECG Compression Based Method.

Science.gov (United States)

Brás, Susana; Ferreira, Jacqueline H T; Soares, Sandra C; Pinho, Armando J

2018-01-01

We present an innovative and robust solution to both biometric and emotion identification using the electrocardiogram (ECG). The ECG represents the electrical signal that comes from the contraction of the heart muscles, indirectly representing the flow of blood inside the heart, it is known to convey a key that allows biometric identification. Moreover, due to its relationship with the nervous system, it also varies as a function of the emotional state. The use of information-theoretic data models, associated with data compression algorithms, allowed to effectively compare ECG records and infer the person identity, as well as emotional state at the time of data collection. The proposed method does not require ECG wave delineation or alignment, which reduces preprocessing error. The method is divided into three steps: (1) conversion of the real-valued ECG record into a symbolic time-series, using a quantization process; (2) conditional compression of the symbolic representation of the ECG, using the symbolic ECG records stored in the database as reference; (3) identification of the ECG record class, using a 1-NN (nearest neighbor) classifier. We obtained over 98% of accuracy in biometric identification, whereas in emotion recognition we attained over 90%. Therefore, the method adequately identify the person, and his/her emotion. Also, the proposed method is flexible and may be adapted to different problems, by the alteration of the templates for training the model.
Biometric template revocation

Science.gov (United States)

Arndt, Craig M.

2004-08-01

Biometric are a powerful technology for identifying humans both locally and at a distance. In order to perform identification or verification biometric systems capture an image of some biometric of a user or subject. The image is then converted mathematical to representation of the person call a template. Since we know that every human in the world is different each human will have different biometric images (different fingerprints, or faces, etc.). This is what makes biometrics useful for identification. However unlike a credit card number or a password to can be given to a person and later revoked if it is compromised and biometric is with the person for life. The problem then is to develop biometric templates witch can be easily revoked and reissued which are also unique to the user and can be easily used for identification and verification. In this paper we develop and present a method to generate a set of templates which are fully unique to the individual and also revocable. By using bases set compression algorithms in an n-dimensional orthogonal space we can represent a give biometric image in an infinite number of equally valued and unique ways. The verification and biometric matching system would be presented with a given template and revocation code. The code will then representing where in the sequence of n-dimensional vectors to start the recognition.
Method and system for normalizing biometric variations to authenticate users from a public database and that ensures individual biometric data privacy

Science.gov (United States)

Strait, Robert S.; Pearson, Peter K.; Sengupta, Sailes K.

2000-01-01

A password system comprises a set of codewords spaced apart from one another by a Hamming distance (HD) that exceeds twice the variability that can be projected for a series of biometric measurements for a particular individual and that is less than the HD that can be encountered between two individuals. To enroll an individual, a biometric measurement is taken and exclusive-ORed with a random codeword to produce a "reference value." To verify the individual later, a biometric measurement is taken and exclusive-ORed with the reference value to reproduce the original random codeword or its approximation. If the reproduced value is not a codeword, the nearest codeword to it is found, and the bits that were corrected to produce the codeword to it is found, and the bits that were corrected to produce the codeword are also toggled in the biometric measurement taken and the codeword generated during enrollment. The correction scheme can be implemented by any conventional error correction code such as Reed-Muller code R(m,n). In the implementation using a hand geometry device an R(2,5) code has been used in this invention. Such codeword and biometric measurement can then be used to see if the individual is an authorized user. Conventional Diffie-Hellman public key encryption schemes and hashing procedures can then be used to secure the communications lines carrying the biometric information and to secure the database of authorized users.
Method and system for normalizing biometric variations to authenticate users from a public database and that ensures individual biometric data privacy

International Nuclear Information System (INIS)

Strait, R.S.; Pearson, P.K.; Sengupta, S.K.

2000-01-01

A password system comprises a set of codewords spaced apart from one another by a Hamming distance (HD) that exceeds twice the variability that can be projected for a series of biometric measurements for a particular individual and that is less than the HD that can be encountered between two individuals. To enroll an individual, a biometric measurement is taken and exclusive-ORed with a random codeword to produce a reference value. To verify the individual later, a biometric measurement is taken and exclusive-ORed with the reference value to reproduce the original random codeword or its approximation. If the reproduced value is not a codeword, the nearest codeword to it is found, and the bits that were corrected to produce the codeword to it is found, and the bits that were corrected to produce the codeword are also toggled in the biometric measurement taken and the codeword generated during enrollment. The correction scheme can be implemented by any conventional error correction code such as Reed-Muller code R(m,n). In the implementation using a hand geometry device an R(2,5) code has been used in this invention. Such codeword and biometric measurement can then be used to see if the individual is an authorized user. Conventional Diffie-Hellman public key encryption schemes and hashing procedures can then be used to secure the communications lines carrying the biometric information and to secure the database of authorized users
Biometrics in Forensic Science: Challenges, Lessons and New Technologies

NARCIS (Netherlands)

Tistarelli, Massimo; Grosso, Enrico; Meuwly, Didier

2014-01-01

Biometrics has historically found its natural mate in Forensics. The first applications found in the literature and over cited so many times, are related to biometric measurements for the identification of multiple offenders from some of their biometric and anthropometric characteristics (tenprint
Biometrics: libraries have begun to see the value of biometrics

OpenAIRE

Panneerselvam, Selvi, M. G.

2007-01-01

It explains the Biometric Technologies which are becoming the foundation of an extensive array of highly secure identification and personal verification solution. Biometric devices with special reference to finger print recognition is dealt in detail. The benefits of Biometrics in Libraries, its employees and members are highlighted.

Biometric Template Security

OpenAIRE

Abhishek Nagar; Karthik Nandakumar; Anil K. Jain

2008-01-01

Biometric recognition offers a reliable solution to the problem of user authentication in identity management systems. With the widespread deployment of biometric systems in various applications, there are increasing concerns about the security and privacy of biometric technology. Public acceptance of biometrics technology will depend on the ability of system designers to demonstrate that these systems are robust, have low error rates, and are tamper proof. We present a high-level categorizat...
Mobile networks for biometric data analysis

CERN Document Server

Madrid, Natividad; Seepold, Ralf; Orcioni, Simone

2016-01-01

This book showcases new and innovative approaches to biometric data capture and analysis, focusing especially on those that are characterized by non-intrusiveness, reliable prediction algorithms, and high user acceptance. It comprises the peer-reviewed papers from the international workshop on the subject that was held in Ancona, Italy, in October 2014 and featured sessions on ICT for health care, biometric data in automotive and home applications, embedded systems for biometric data analysis, biometric data analysis: EMG and ECG, and ICT for gait analysis. The background to the book is the challenge posed by the prevention and treatment of common, widespread chronic diseases in modern, aging societies. Capture of biometric data is a cornerstone for any analysis and treatment strategy. The latest advances in sensor technology allow accurate data measurement in a non-intrusive way, and in many cases it is necessary to provide online monitoring and real-time data capturing to support a patient’s prevention pl...
Biometric and Emotion Identification: An ECG Compression Based Method

Directory of Open Access Journals (Sweden)

Susana Brás

2018-04-01

Full Text Available We present an innovative and robust solution to both biometric and emotion identification using the electrocardiogram (ECG. The ECG represents the electrical signal that comes from the contraction of the heart muscles, indirectly representing the flow of blood inside the heart, it is known to convey a key that allows biometric identification. Moreover, due to its relationship with the nervous system, it also varies as a function of the emotional state. The use of information-theoretic data models, associated with data compression algorithms, allowed to effectively compare ECG records and infer the person identity, as well as emotional state at the time of data collection. The proposed method does not require ECG wave delineation or alignment, which reduces preprocessing error. The method is divided into three steps: (1 conversion of the real-valued ECG record into a symbolic time-series, using a quantization process; (2 conditional compression of the symbolic representation of the ECG, using the symbolic ECG records stored in the database as reference; (3 identification of the ECG record class, using a 1-NN (nearest neighbor classifier. We obtained over 98% of accuracy in biometric identification, whereas in emotion recognition we attained over 90%. Therefore, the method adequately identify the person, and his/her emotion. Also, the proposed method is flexible and may be adapted to different problems, by the alteration of the templates for training the model.
Biometric and Emotion Identification: An ECG Compression Based Method

Science.gov (United States)

Brás, Susana; Ferreira, Jacqueline H. T.; Soares, Sandra C.; Pinho, Armando J.

2018-01-01

We present an innovative and robust solution to both biometric and emotion identification using the electrocardiogram (ECG). The ECG represents the electrical signal that comes from the contraction of the heart muscles, indirectly representing the flow of blood inside the heart, it is known to convey a key that allows biometric identification. Moreover, due to its relationship with the nervous system, it also varies as a function of the emotional state. The use of information-theoretic data models, associated with data compression algorithms, allowed to effectively compare ECG records and infer the person identity, as well as emotional state at the time of data collection. The proposed method does not require ECG wave delineation or alignment, which reduces preprocessing error. The method is divided into three steps: (1) conversion of the real-valued ECG record into a symbolic time-series, using a quantization process; (2) conditional compression of the symbolic representation of the ECG, using the symbolic ECG records stored in the database as reference; (3) identification of the ECG record class, using a 1-NN (nearest neighbor) classifier. We obtained over 98% of accuracy in biometric identification, whereas in emotion recognition we attained over 90%. Therefore, the method adequately identify the person, and his/her emotion. Also, the proposed method is flexible and may be adapted to different problems, by the alteration of the templates for training the model. PMID:29670564
Efficient and privacy-preserving biometric identification in cloud

Directory of Open Access Journals (Sweden)

Changhee Hahn

2016-09-01

Full Text Available With the rapid growth in the development of smart devices equipped with biometric sensors, client identification system using biometric traits are widely adopted across various applications. Among many biometric traits, fingerprint-based identification systems have been extensively studied and deployed. However, to adopt biometric identification systems in practical applications, two main obstacles in terms of efficiency and client privacy must be resolved simultaneously. That is, identification should be performed at an acceptable time, and only a client should have access to his/her biometric traits, which are not revocable if leaked. Until now, multiple studies have demonstrated successful protection of client biometric data; however, such systems lack efficiency that leads to excessive time utilization for identification. The most recently researched scheme shows efficiency improvements but reveals client biometric traits to other entities such as biometric database server. This violates client privacy. In this paper, we propose an efficient and privacy-preserving fingerprint identification scheme by using cloud systems. The proposed scheme extensively exploits the computation power of a cloud so that most of the laborious computations are performed by the cloud service provider. According to our experimental results on an Amazon EC2 cloud, the proposed scheme is faster than the existing schemes and guarantees client privacy by exploiting symmetric homomorphic encryption. Our security analysis shows that during identification, the client fingerprint data is not disclosed to the cloud service provider or fingerprint database server.
Multimodal Biometric System- Fusion Of Face And Fingerprint Biometrics At Match Score Fusion Level

OpenAIRE

Grace Wangari Mwaura; Prof. Waweru Mwangi; Dr. Calvins Otieno

2017-01-01

Biometrics has developed to be one of the most relevant technologies used in Information Technology IT security. Unimodal biometric systems have a variety of problems which decreases the performance and accuracy of these system. One way to overcome the limitations of the unimodal biometric systems is through fusion to form a multimodal biometric system. Generally biometric fusion is defined as the use of multiple types of biometric data or ways of processing the data to improve the performanc...
Biometric templates selection and update using quality measures

Science.gov (United States)

Abboud, Ali J.; Jassim, Sabah A.

2012-06-01

To deal with severe variation in recording conditions, most biometric systems acquire multiple biometric samples, at the enrolment stage, for the same person and then extract their individual biometric feature vectors and store them in the gallery in the form of biometric template(s), labelled with the person's identity. The number of samples/templates and the choice of the most appropriate templates influence the performance of the system. The desired biometric template(s) selection technique must aim to control the run time and storage requirements while improving the recognition accuracy of the biometric system. This paper is devoted to elaborating on and discussing a new two stages approach for biometric templates selection and update. This approach uses a quality-based clustering, followed by a special criterion for the selection of an ultimate set of biometric templates from the various clusters. This approach is developed to select adaptively a specific number of templates for each individual. The number of biometric templates depends mainly on the performance of each individual (i.e. gallery size should be optimised to meet the needs of each target individual). These experiments have been conducted on two face image databases and their results will demonstrate the effectiveness of proposed quality-guided approach.
Biometrics and Identity Management

DEFF Research Database (Denmark)

management. BIOID 2008. The papers are categorized in four classes. These classes represent the 4 working groups of the COST Action 2101. For more information, see http://www.cost2101.org/. Biometric data quality and multimodal biometric templates, Unsupervised interactive interfaces for multimodal...... security and border control scenarios it is now apparent that the widespread availability of biometrics in everyday life will also spin out an ever increasing number of (private) applications in other domains. Crucial to this vision is the management of the user's identity, which does not only imply...... biometrics, Biometric attacks and countermeasures, Standards and privacy issues for biometrics in identity documents and smart cards. BIOID 2008 is an initiative of the COST Action 2101 on Biometrics for Identity Documents and Smart Cards. It is supported by the EU Framework 7 Programme. Other sponsors...
Biometrics: Multi-Service Tactics, Techniques, and Procedures for Tactical Employment of Biometrics in Support of Operations

Science.gov (United States)

2016-05-01

Biometrics in Support of Operations Biometrics -at-Sea: Business Rules for South Florida United States...Intelligence Activities Biometrics -Enabled Intelligence USCG Biometrics -at-Sea: Business Rules for...Defense Biometrics United States Intelligence Activities Active Army,
Biometrics Theory, Methods, and Applications

CERN Document Server

Boulgouris, N V; Micheli-Tzanakou, Evangelia

2009-01-01

An in-depth examination of the cutting edge of biometrics. This book fills a gap in the literature by detailing the recent advances and emerging theories, methods, and applications of biometric systems in a variety of infrastructures. Edited by a panel of experts, it provides comprehensive coverage of:. Multilinear discriminant analysis for biometric signal recognition;. Biometric identity authentication techniques based on neural networks;. Multimodal biometrics and design of classifiers for biometric fusion;. Feature selection and facial aging modeling for face recognition;. Geometrical and
Bartus Iris biometrics

Energy Technology Data Exchange (ETDEWEB)

Johnston, R.; Grace, W.

1996-07-01

This is the final report of a one-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). We won a 1994 R&D 100 Award for inventing the Bartas Iris Verification System. The system has been delivered to a sponsor and is no longer available to us. This technology can verify the identity of a person for purposes of access control, national security, law enforcement, forensics, counter-terrorism, and medical, financial, or scholastic records. The technique is non-invasive, psychologically acceptable, works in real-time, and obtains more biometric data than any other biometric except DNA analysis. This project sought to develop a new, second-generation prototype instrument.
Biometric Technologies and Verification Systems

CERN Document Server

Vacca, John R

2007-01-01

Biometric Technologies and Verification Systems is organized into nine parts composed of 30 chapters, including an extensive glossary of biometric terms and acronyms. It discusses the current state-of-the-art in biometric verification/authentication, identification and system design principles. It also provides a step-by-step discussion of how biometrics works; how biometric data in human beings can be collected and analyzed in a number of ways; how biometrics are currently being used as a method of personal identification in which people are recognized by their own unique corporal or behavior
Selectively Encrypted Pull-Up Based Watermarking of Biometric data

Science.gov (United States)

Shinde, S. A.; Patel, Kushal S.

2012-10-01

Biometric authentication systems are becoming increasingly popular due to their potential usage in information security. However, digital biometric data (e.g. thumb impression) are themselves vulnerable to security attacks. There are various methods are available to secure biometric data. In biometric watermarking the data are embedded in an image container and are only retrieved if the secrete key is available. This container image is encrypted to have more security against the attack. As wireless devices are equipped with battery as their power supply, they have limited computational capabilities; therefore to reduce energy consumption we use the method of selective encryption of container image. The bit pull-up-based biometric watermarking scheme is based on amplitude modulation and bit priority which reduces the retrieval error rate to great extent. By using selective Encryption mechanism we expect more efficiency in time at the time of encryption as well as decryption. Significant reduction in error rate is expected to be achieved by the bit pull-up method.
Biometric citizenship and alienage

DEFF Research Database (Denmark)

Stenum, Helle

. This paper asks if and how biometric techniques are the basis of a re-structuring of management of migration and mobility: Is the suggestion of biometric identifiers reflecting the withdrawal from the principle of rights applied to human beings as an abstract of the universal individual all being equal......, to the (re)introduction the concept of rights being engraved in your body, depended first and foremost on one’s birth, kinship and geography ? The paper will discuss biometric technology in a historical context and explore the apparent biometric divide between citizens and migrants, the latter positioned......Biometric identifiers (finger prints, face scans, iris scans etc.) have increasingly become a key element in technology of EU border and migration management. SIS II, EURODAC and VIS are centralized systems that contain fingerprints of different groups of non-EU citizen, and the biometric...
The biometric recognition on contactless multi-spectrum finger images

Science.gov (United States)

Kang, Wenxiong; Chen, Xiaopeng; Wu, Qiuxia

2015-01-01

This paper presents a novel multimodal biometric system based on contactless multi-spectrum finger images, which aims to deal with the limitations of unimodal biometrics. The chief merits of the system are the richness of the permissible texture and the ease of data access. We constructed a multi-spectrum instrument to simultaneously acquire three different types of biometrics from a finger: contactless fingerprint, finger vein, and knuckleprint. On the basis of the samples with these characteristics, a moderate database was built for the evaluation of our system. Considering the real-time requirements and the respective characteristics of the three biometrics, the block local binary patterns algorithm was used to extract features and match for the fingerprints and finger veins, while the Oriented FAST and Rotated BRIEF algorithm was applied for knuckleprints. Finally, score-level fusion was performed on the matching results from the aforementioned three types of biometrics. The experiments showed that our proposed multimodal biometric recognition system achieves an equal error rate of 0.109%, which is 88.9%, 94.6%, and 89.7% lower than the individual fingerprint, knuckleprint, and finger vein recognitions, respectively. Nevertheless, our proposed system also satisfies the real-time requirements of the applications.
Beyond Biometrics

NARCIS (Netherlands)

van den Broek, Egon

Throughout the last 40 years, the essence of automated identification of users has remained the same. In this article, a new class of biometrics is proposed that is founded on processing biosignals, as opposed to images. After a brief introduction on biometrics, biosignals are discussed, including
Biometric systems - possibilities and dangers

OpenAIRE

Petržilka, Jakub

2013-01-01

This bachelor thesis is focused on biometric methods, particularly on fingerprint recognition. First part of thesis places biometric into other methods of people's identification. Identification by token and by knowledge. It also describes the beginning and evolution of biometric. The theoretical part also closely clarify working with data and different view on the biometric systems. The following part of the thesis defines the basic principles of using biometric systems, counting FAR and FRR...
BIOMETRIC CRYPTOGRAPHY AND NETWORK AUTHENTICATION

Directory of Open Access Journals (Sweden)

Tonimir Kišasondi

2007-06-01

Full Text Available In this paper we will present some schemes for strengthening network authentification over insecure channels with biometric concepts or how to securely transfer or use biometric characteristics as cryptographic keys. We will show why some current authentification schemes are insufficient and we will present our concepts of biometric hashes and authentification that rely on unimodal and multimodal biometrics. Our concept can be applied on any biometric authentification scheme and is universal for all systems.
Signal and image processing for biometrics

CERN Document Server

Proença, Hugo; Du, Eliza

2014-01-01

This volume offers a guide to the state of the art in the fast evolving field of biometric recognition to newcomers and experienced practitioners. It is focused on the emerging strategies to perform biometric recognition under uncontrolled data acquisition conditions. The mainstream research work in this field is presented in an organized manner, so the reader can easily follow the trends that best suits her/his interests in this growing field. The book chapters cover the recent advances in less controlled / covert data acquisition frameworks, segmentation of poor quality biometric data, biometric data quality assessment, normalization of poor quality biometric data. contactless biometric recognition strategies, biometric recognition robustness, data resolution, illumination, distance, pose, motion, occlusions, multispectral biometric recognition, multimodal biometrics, fusion at different levels, high confidence automatic surveillance.
Multimodal Biometric System- Fusion Of Face And Fingerprint Biometrics At Match Score Fusion Level

Directory of Open Access Journals (Sweden)

Grace Wangari Mwaura

2017-04-01

Full Text Available Biometrics has developed to be one of the most relevant technologies used in Information Technology IT security. Unimodal biometric systems have a variety of problems which decreases the performance and accuracy of these system. One way to overcome the limitations of the unimodal biometric systems is through fusion to form a multimodal biometric system. Generally biometric fusion is defined as the use of multiple types of biometric data or ways of processing the data to improve the performance of biometric systems. This paper proposes to develop a model for fusion of the face and fingerprint biometric at the match score fusion level. The face and fingerprint unimodal in the proposed model are built using scale invariant feature transform SIFT algorithm and the hamming distance to measure the distance between key points. To evaluate the performance of the multimodal system the FAR and FRR of the multimodal are compared along those of the individual unimodal systems. It has been established that the multimodal has a higher accuracy of 92.5 compared to the face unimodal system at 90 while the fingerprint unimodal system is at 82.5.

Gas discharge visualization: an imaging and modeling tool for medical biometrics.

Science.gov (United States)

Kostyuk, Nataliya; Cole, Phyadragren; Meghanathan, Natarajan; Isokpehi, Raphael D; Cohly, Hari H P

2011-01-01

The need for automated identification of a disease makes the issue of medical biometrics very current in our society. Not all biometric tools available provide real-time feedback. We introduce gas discharge visualization (GDV) technique as one of the biometric tools that have the potential to identify deviations from the normal functional state at early stages and in real time. GDV is a nonintrusive technique to capture the physiological and psychoemotional status of a person and the functional status of different organs and organ systems through the electrophotonic emissions of fingertips placed on the surface of an impulse analyzer. This paper first introduces biometrics and its different types and then specifically focuses on medical biometrics and the potential applications of GDV in medical biometrics. We also present our previous experience with GDV in the research regarding autism and the potential use of GDV in combination with computer science for the potential development of biological pattern/biomarker for different kinds of health abnormalities including cancer and mental diseases.
Touchless fingerprint biometrics

CERN Document Server

Labati, Ruggero Donida; Scotti, Fabio

2015-01-01

Offering the first comprehensive analysis of touchless fingerprint-recognition technologies, Touchless Fingerprint Biometrics gives an overview of the state of the art and describes relevant industrial applications. It also presents new techniques to efficiently and effectively implement advanced solutions based on touchless fingerprinting.The most accurate current biometric technologies in touch-based fingerprint-recognition systems require a relatively high level of user cooperation to acquire samples of the concerned biometric trait. With the potential for reduced constraints, reduced hardw
Analysis and comparison of biometric methods

OpenAIRE

Zatloukal, Filip

2011-01-01

The thesis deals with biometrics and biometric systems and the possibility to use these systems in the enterprise. Aim of this study is an analysis and description of selected types of biometric identification methods and their advantages and shortcomings. The work is divided into two parts. The first part is theoretical, describes the basic concepts of biometrics, biometric identification criteria, currently used identification systems, the ways of biometric systems use, performance measurem...
Modeling long-term human activeness using recurrent neural networks for biometric data.

Science.gov (United States)

Kim, Zae Myung; Oh, Hyungrai; Kim, Han-Gyu; Lim, Chae-Gyun; Oh, Kyo-Joong; Choi, Ho-Jin

2017-05-18

With the invention of fitness trackers, it has been possible to continuously monitor a user's biometric data such as heart rates, number of footsteps taken, and amount of calories burned. This paper names the time series of these three types of biometric data, the user's "activeness", and investigates the feasibility in modeling and predicting the long-term activeness of the user. The dataset used in this study consisted of several months of biometric time-series data gathered by seven users independently. Four recurrent neural network (RNN) architectures-as well as a deep neural network and a simple regression model-were proposed to investigate the performance on predicting the activeness of the user under various length-related hyper-parameter settings. In addition, the learned model was tested to predict the time period when the user's activeness falls below a certain threshold. A preliminary experimental result shows that each type of activeness data exhibited a short-term autocorrelation; and among the three types of data, the consumed calories and the number of footsteps were positively correlated, while the heart rate data showed almost no correlation with neither of them. It is probably due to this characteristic of the dataset that although the RNN models produced the best results on modeling the user's activeness, the difference was marginal; and other baseline models, especially the linear regression model, performed quite admirably as well. Further experimental results show that it is feasible to predict a user's future activeness with precision, for example, a trained RNN model could predict-with the precision of 84%-when the user would be less active within the next hour given the latest 15 min of his activeness data. This paper defines and investigates the notion of a user's "activeness", and shows that forecasting the long-term activeness of the user is indeed possible. Such information can be utilized by a health-related application to proactively
Comparative and Analysis of Biometric Systems

OpenAIRE

Manivannan,; Padma

2011-01-01

Biometric as the science of recognizing an individual based on his or her physical or behavioral traits, it is beginning to gain acceptance as a legitimate method for determining an individual identity.Biometric have now been deployed in various commercial, civilian, and national security applications. Biometric described overview of various biometric techniques and the need to be addressed form making biometric technology an effective tool for providing information security.
The research and application of multi-biometric acquisition embedded system

Science.gov (United States)

Deng, Shichao; Liu, Tiegen; Guo, Jingjing; Li, Xiuyan

2009-11-01

The identification technology based on multi-biometric can greatly improve the applicability, reliability and antifalsification. This paper presents a multi-biometric system bases on embedded system, which includes: three capture daughter boards are applied to obtain different biometric: one each for fingerprint, iris and vein of the back of hand; FPGA (Field Programmable Gate Array) is designed as coprocessor, which uses to configure three daughter boards on request and provides data path between DSP (digital signal processor) and daughter boards; DSP is the master processor and its functions include: control the biometric information acquisition, extracts feature as required and responsible for compare the results with the local database or data server through network communication. The advantages of this system were it can acquire three different biometric in real time, extracts complexity feature flexibly in different biometrics' raw data according to different purposes and arithmetic and network interface on the core-board will be the solution of big data scale. Because this embedded system has high stability, reliability, flexibility and fit for different data scale, it can satisfy the demand of multi-biometric recognition.
The biometric-based module of smart grid system

Science.gov (United States)

Engel, E.; Kovalev, I. V.; Ermoshkina, A.

2015-10-01

Within Smart Grid concept the flexible biometric-based module base on Principal Component Analysis (PCA) and selective Neural Network is developed. The formation of the selective Neural Network the biometric-based module uses the method which includes three main stages: preliminary processing of the image, face localization and face recognition. Experiments on the Yale face database show that (i) selective Neural Network exhibits promising classification capability for face detection, recognition problems; and (ii) the proposed biometric-based module achieves near real-time face detection, recognition speed and the competitive performance, as compared to some existing subspaces-based methods.
Secure biometric image sensor and authentication scheme based on compressed sensing.

Science.gov (United States)

Suzuki, Hiroyuki; Suzuki, Masamichi; Urabe, Takuya; Obi, Takashi; Yamaguchi, Masahiro; Ohyama, Nagaaki

2013-11-20

It is important to ensure the security of biometric authentication information, because its leakage causes serious risks, such as replay attacks using the stolen biometric data, and also because it is almost impossible to replace raw biometric information. In this paper, we propose a secure biometric authentication scheme that protects such information by employing an optical data ciphering technique based on compressed sensing. The proposed scheme is based on two-factor authentication, the biometric information being supplemented by secret information that is used as a random seed for a cipher key. In this scheme, a biometric image is optically encrypted at the time of image capture, and a pair of restored biometric images for enrollment and verification are verified in the authentication server. If any of the biometric information is exposed to risk, it can be reenrolled by changing the secret information. Through numerical experiments, we confirm that finger vein images can be restored from the compressed sensing measurement data. We also present results that verify the accuracy of the scheme.
The PLR-DTW method for ECG based biometric identification.

Science.gov (United States)

Shen, Jun; Bao, Shu-Di; Yang, Li-Cai; Li, Ye

2011-01-01

There has been a surge of research on electrocardiogram (ECG) signal based biometric for person identification. Though most of the existing studies claimed that ECG signal is unique to an individual and can be a viable biometric, one of the main difficulties for real-world applications of ECG biometric is the accuracy performance. To address this problem, this study proposes a PLR-DTW method for ECG biometric, where the Piecewise Linear Representation (PLR) is used to keep important information of an ECG signal segment while reduce the data dimension at the same time if necessary, and the Dynamic Time Warping (DTW) is used for similarity measures between two signal segments. The performance evaluation was carried out on three ECG databases, and the existing method using wavelet coefficients, which was proved to have good accuracy performance, was selected for comparison. The analysis results show that the PLR-DTW method achieves an accuracy rate of 100% for identification, while the one using wavelet coefficients achieved only around 93%.
Modular biometric system

Science.gov (United States)

Hsu, Charles; Viazanko, Michael; O'Looney, Jimmy; Szu, Harold

2009-04-01

Modularity Biometric System (MBS) is an approach to support AiTR of the cooperated and/or non-cooperated standoff biometric in an area persistent surveillance. Advanced active and passive EOIR and RF sensor suite is not considered here. Neither will we consider the ROC, PD vs. FAR, versus the standoff POT in this paper. Our goal is to catch the "most wanted (MW)" two dozens, separately furthermore ad hoc woman MW class from man MW class, given their archrivals sparse front face data basis, by means of various new instantaneous input called probing faces. We present an advanced algorithm: mini-Max classifier, a sparse sample realization of Cramer-Rao Fisher bound of the Maximum Likelihood classifier that minimize the dispersions among the same woman classes and maximize the separation among different man-woman classes, based on the simple feature space of MIT Petland eigen-faces. The original aspect consists of a modular structured design approach at the system-level with multi-level architectures, multiple computing paradigms, and adaptable/evolvable techniques to allow for achieving a scalable structure in terms of biometric algorithms, identification quality, sensors, database complexity, database integration, and component heterogenity. MBS consist of a number of biometric technologies including fingerprints, vein maps, voice and face recognitions with innovative DSP algorithm, and their hardware implementations such as using Field Programmable Gate arrays (FPGAs). Biometric technologies and the composed modularity biometric system are significant for governmental agencies, enterprises, banks and all other organizations to protect people or control access to critical resources.
On Biometrics With Eye Movements.

Science.gov (United States)

Zhang, Youming; Juhola, Martti

2017-09-01

Eye movements are a relatively novel data source for biometric identification. When video cameras applied to eye tracking become smaller and more efficient, this data source could offer interesting opportunities for the development of eye movement biometrics. In this paper, we study primarily biometric identification as seen as a classification task of multiple classes, and secondarily biometric verification considered as binary classification. Our research is based on the saccadic eye movement signal measurements from 109 young subjects. In order to test the data measured, we use a procedure of biometric identification according to the one-versus-one (subject) principle. In a development from our previous research, which also involved biometric verification based on saccadic eye movements, we now apply another eye movement tracker device with a higher sampling frequency of 250 Hz. The results obtained are good, with correct identification rates at 80-90% at their best.
Biometrics and privacy

NARCIS (Netherlands)

Grijpink, J.H.A.M.

2001-01-01

Biometrics offers many alternatives for protecting our privacy and preventing us from falling victim to crime. Biometrics can even serve as a solid basis for safe anonymous and semi-anonymous legal transactions. In this article Jan Grijpink clarifies which concepts and practical applications this
Emerging Biometric Modalities: Challenges and Opportunities

Science.gov (United States)

Gafurov, Davrondzhon

Recent advances in sensor technology and wide spread use of various electronics (computers, PDA, mobile phones etc.) provide new opportunities for capturing and analyses of novel physiological and behavioural traits of human beings for biometric authentication. This paper presents an overview of several such types of human characteristics that have been proposed as alternatives to traditional types of biometrics. We refer to these characteristics as emerging biometrics. We survey various types of emerging modalities and techniques, and discuss their pros and cons. Emerging biometrics faces several limitations and challenges which include subject population coverage (focusing mostly on adults); unavailability of benchmark databases; little research with respect to vulnerability/robustness against attacks; and some privacy concerns they may arise. In addition, recognition performance of emerging modalities are generally less accurate compared to the traditional biometrics. Despite all of these emerging biometrics posses their own benefits and advantages compared to traditional biometrics which makes them still attractive for research. First of all, emerging biometrics can always serve as a complementary source for identity information; they can be suitable in applications where traditional biometrics are difficult or impossible to adapt such as continuous or periodic re-verification of the user's identity etc.
Combining Cryptography with EEG Biometrics.

Science.gov (United States)

Damaševičius, Robertas; Maskeliūnas, Rytis; Kazanavičius, Egidijus; Woźniak, Marcin

2018-01-01

Cryptographic frameworks depend on key sharing for ensuring security of data. While the keys in cryptographic frameworks must be correctly reproducible and not unequivocally connected to the identity of a user, in biometric frameworks this is different. Joining cryptography techniques with biometrics can solve these issues. We present a biometric authentication method based on the discrete logarithm problem and Bose-Chaudhuri-Hocquenghem (BCH) codes, perform its security analysis, and demonstrate its security characteristics. We evaluate a biometric cryptosystem using our own dataset of electroencephalography (EEG) data collected from 42 subjects. The experimental results show that the described biometric user authentication system is effective, achieving an Equal Error Rate (ERR) of 0.024.
Biometrics: Accessibility challenge or opportunity?

Science.gov (United States)

Blanco-Gonzalo, Ramon; Lunerti, Chiara; Sanchez-Reillo, Raul; Guest, Richard Michael

2018-01-01

Biometric recognition is currently implemented in several authentication contexts, most recently in mobile devices where it is expected to complement or even replace traditional authentication modalities such as PIN (Personal Identification Number) or passwords. The assumed convenience characteristics of biometrics are transparency, reliability and ease-of-use, however, the question of whether biometric recognition is as intuitive and straightforward to use is open to debate. Can biometric systems make some tasks easier for people with accessibility concerns? To investigate this question, an accessibility evaluation of a mobile app was conducted where test subjects withdraw money from a fictitious ATM (Automated Teller Machine) scenario. The biometric authentication mechanisms used include face, voice, and fingerprint. Furthermore, we employed traditional modalities of PIN and pattern in order to check if biometric recognition is indeed a real improvement. The trial test subjects within this work were people with real-life accessibility concerns. A group of people without accessibility concerns also participated, providing a baseline performance. Experimental results are presented concerning performance, HCI (Human-Computer Interaction) and accessibility, grouped according to category of accessibility concern. Our results reveal links between individual modalities and user category establishing guidelines for future accessible biometric products.
Biometrics: Accessibility challenge or opportunity?

Science.gov (United States)

Lunerti, Chiara; Sanchez-Reillo, Raul; Guest, Richard Michael

2018-01-01

Biometric recognition is currently implemented in several authentication contexts, most recently in mobile devices where it is expected to complement or even replace traditional authentication modalities such as PIN (Personal Identification Number) or passwords. The assumed convenience characteristics of biometrics are transparency, reliability and ease-of-use, however, the question of whether biometric recognition is as intuitive and straightforward to use is open to debate. Can biometric systems make some tasks easier for people with accessibility concerns? To investigate this question, an accessibility evaluation of a mobile app was conducted where test subjects withdraw money from a fictitious ATM (Automated Teller Machine) scenario. The biometric authentication mechanisms used include face, voice, and fingerprint. Furthermore, we employed traditional modalities of PIN and pattern in order to check if biometric recognition is indeed a real improvement. The trial test subjects within this work were people with real-life accessibility concerns. A group of people without accessibility concerns also participated, providing a baseline performance. Experimental results are presented concerning performance, HCI (Human-Computer Interaction) and accessibility, grouped according to category of accessibility concern. Our results reveal links between individual modalities and user category establishing guidelines for future accessible biometric products. PMID:29565989
Biometric identification using local iterated function

Science.gov (United States)

Al-Saidi, N. M. G.; Said, M. R. M.

2014-06-01

Biometric identification protocol has been received an increasing interest recently. It is a process that determines person identity by making use of their biometric features. A new biometric identification method is presented in this paper based on partial self-similarity that used to identify features within fingerprint images. This approach is already used in Fractal Image Compression (FIC) due to their ability to represent the images by a limited number of affine transformations, and its variation of scale, translation or rotation. These features give the recognition process high impact and good performance. To process data in a fingerprint image, it first converted into digital format using Optical Fingerprint Reader (OFR). The verification process is done by comparing these data with the server data. The system analysis shows that the proposed method is efficient in terms of memory and time complexity.
On Soft Biometrics

DEFF Research Database (Denmark)

Nixon, Mark; Correia, Paulo; Nasrollahi, Kamal

2015-01-01

Innovation has formed much of the rich history in biometrics. The field of soft biometrics was originally aimed to augment the recognition process by fusion of metrics that were sufficient to discriminate populations rather than individuals. This was later refined to use measures that could be us...
Review of modern biometric user authentication and their development prospects

Science.gov (United States)

Boriev, Z. V.; Sokolov, S. S.; Nyrkov, A. P.

2015-09-01

This article discusses the possibility of using biometric information technologies in management. Made a brief overview of access control and time attendance. Analyzed biometrics and identification system user. Recommendations on the use of various systems depending on the specific tasks.
Age factors in biometric processing

CERN Document Server

Fairhurst, Michael

2013-01-01

As biometrics-based identification and identity authentication become increasingly widespread in their deployment, it becomes correspondingly important to consider more carefully issues relating to reliability, usability and inclusion. One factor which is particularly important in this context is that of the relationship between the nature of the measurements extracted from a particular biometric modality and the age of the sample donor, and the effect which age has on physiological and behavioural characteristics invoked in a biometric transaction. In Age Factors in Biometric Processing an in

A bimodal biometric identification system

Science.gov (United States)

Laghari, Mohammad S.; Khuwaja, Gulzar A.

2013-03-01

Biometrics consists of methods for uniquely recognizing humans based upon one or more intrinsic physical or behavioral traits. Physicals are related to the shape of the body. Behavioral are related to the behavior of a person. However, biometric authentication systems suffer from imprecision and difficulty in person recognition due to a number of reasons and no single biometrics is expected to effectively satisfy the requirements of all verification and/or identification applications. Bimodal biometric systems are expected to be more reliable due to the presence of two pieces of evidence and also be able to meet the severe performance requirements imposed by various applications. This paper presents a neural network based bimodal biometric identification system by using human face and handwritten signature features.
Applying intelligent statistical methods on biometric systems

OpenAIRE

Betschart, Willie

2005-01-01

This master’s thesis work was performed at Optimum Biometric Labs, OBL, located in Karlskrona, Sweden. Optimum Biometric Labs perform independent scenario evaluations to companies who develop biometric devices. The company has a product Optimum preConTM which is surveillance and diagnosis tool for biometric systems. This thesis work’s objective was to develop a conceptual model and implement it as an additional layer above the biometric layer with intelligence about the biometric users. The l...
A method of ECG template extraction for biometrics applications.

Science.gov (United States)

Zhou, Xiang; Lu, Yang; Chen, Meng; Bao, Shu-Di; Miao, Fen

2014-01-01

ECG has attracted widespread attention as one of the most important non-invasive physiological signals in healthcare-system related biometrics for its characteristics like ease-of-monitoring, individual uniqueness as well as important clinical value. This study proposes a method of dynamic threshold setting to extract the most stable ECG waveform as the template for the consequent ECG identification process. With the proposed method, the accuracy of ECG biometrics using the dynamic time wraping for difference measures has been significantly improved. Analysis results with the self-built electrocardiogram database show that the deployment of the proposed method was able to reduce the half total error rate of the ECG biometric system from 3.35% to 1.45%. Its average running time on the platform of android mobile terminal was around 0.06 seconds, and thus demonstrates acceptable real-time performance.
Biometrics: Accessibility challenge or opportunity?

Directory of Open Access Journals (Sweden)

Ramon Blanco-Gonzalo

Full Text Available Biometric recognition is currently implemented in several authentication contexts, most recently in mobile devices where it is expected to complement or even replace traditional authentication modalities such as PIN (Personal Identification Number or passwords. The assumed convenience characteristics of biometrics are transparency, reliability and ease-of-use, however, the question of whether biometric recognition is as intuitive and straightforward to use is open to debate. Can biometric systems make some tasks easier for people with accessibility concerns? To investigate this question, an accessibility evaluation of a mobile app was conducted where test subjects withdraw money from a fictitious ATM (Automated Teller Machine scenario. The biometric authentication mechanisms used include face, voice, and fingerprint. Furthermore, we employed traditional modalities of PIN and pattern in order to check if biometric recognition is indeed a real improvement. The trial test subjects within this work were people with real-life accessibility concerns. A group of people without accessibility concerns also participated, providing a baseline performance. Experimental results are presented concerning performance, HCI (Human-Computer Interaction and accessibility, grouped according to category of accessibility concern. Our results reveal links between individual modalities and user category establishing guidelines for future accessible biometric products.
Can soft biometric traits assist user recognition?

Science.gov (United States)

Jain, Anil K.; Dass, Sarat C.; Nandakumar, Karthik

2004-08-01

Biometrics is rapidly gaining acceptance as the technology that can meet the ever increasing need for security in critical applications. Biometric systems automatically recognize individuals based on their physiological and behavioral characteristics. Hence, the fundamental requirement of any biometric recognition system is a human trait having several desirable properties like universality, distinctiveness, permanence, collectability, acceptability, and resistance to circumvention. However, a human characteristic that possesses all these properties has not yet been identified. As a result, none of the existing biometric systems provide perfect recognition and there is a scope for improving the performance of these systems. Although characteristics like gender, ethnicity, age, height, weight and eye color are not unique and reliable, they provide some information about the user. We refer to these characteristics as "soft" biometric traits and argue that these traits can complement the identity information provided by the primary biometric identifiers like fingerprint and face. This paper presents the motivation for utilizing soft biometric information and analyzes how the soft biometric traits can be automatically extracted and incorporated in the decision making process of the primary biometric system. Preliminary experiments were conducted on a fingerprint database of 160 users by synthetically generating soft biometric traits like gender, ethnicity, and height based on known statistics. The results show that the use of additional soft biometric user information significantly improves (approximately 6%) the recognition performance of the fingerprint biometric system.
Gait biometrics under spoofing attacks: an experimental investigation

Science.gov (United States)

Hadid, Abdenour; Ghahramani, Mohammad; Kellokumpu, Vili; Feng, Xiaoyi; Bustard, John; Nixon, Mark

2015-11-01

Gait is a relatively biometric modality which has a precious advantage over other modalities, such as iris and voice, in that it can be easily captured from a distance. Although it has recently become a topic of great interest in biometric research, there has been little investigation into gait spoofing attacks where a person tries to imitate the clothing or walking style of someone else. We recently analyzed for the first time the effects of spoofing attacks on silhouette-based gait biometric systems and showed that it was indeed possible to spoof gait biometric systems by clothing impersonation and the deliberate selection of a target that has a similar build to the attacker. To gain deeper insight into the performance of current gait biometric systems under spoofing attacks, we provide a thorough investigation on how clothing can be used to spoof a target and evaluate the performance of two state-of-the-art recognition methods on a gait spoofing database recorded at the University of Southampton. Furthermore, we describe and evaluate an initial solution coping with gait spoofing attacks. The obtained results are very promising and point out interesting findings which can be used for future investigations.
Evolutionary Algorithms Application Analysis in Biometric Systems

Directory of Open Access Journals (Sweden)

N. Goranin

2010-01-01

Full Text Available Wide usage of biometric information for person identity verification purposes, terrorist acts prevention measures and authenticationprocess simplification in computer systems has raised significant attention to reliability and efficiency of biometricsystems. Modern biometric systems still face many reliability and efficiency related issues such as reference databasesearch speed, errors while recognizing of biometric information or automating biometric feature extraction. Current scientificinvestigations show that application of evolutionary algorithms may significantly improve biometric systems. In thisarticle we provide a comprehensive review of main scientific research done in sphere of evolutionary algorithm applicationfor biometric system parameter improvement.
Compressed ECG biometric: a fast, secured and efficient method for identification of CVD patient.

Science.gov (United States)

Sufi, Fahim; Khalil, Ibrahim; Mahmood, Abdun

2011-12-01

Adoption of compression technology is often required for wireless cardiovascular monitoring, due to the enormous size of Electrocardiography (ECG) signal and limited bandwidth of Internet. However, compressed ECG must be decompressed before performing human identification using present research on ECG based biometric techniques. This additional step of decompression creates a significant processing delay for identification task. This becomes an obvious burden on a system, if this needs to be done for a trillion of compressed ECG per hour by the hospital. Even though the hospital might be able to come up with an expensive infrastructure to tame the exuberant processing, for small intermediate nodes in a multihop network identification preceded by decompression is confronting. In this paper, we report a technique by which a person can be identified directly from his / her compressed ECG. This technique completely obviates the step of decompression and therefore upholds biometric identification less intimidating for the smaller nodes in a multihop network. The biometric template created by this new technique is lower in size compared to the existing ECG based biometrics as well as other forms of biometrics like face, finger, retina etc. (up to 8302 times lower than face template and 9 times lower than existing ECG based biometric template). Lower size of the template substantially reduces the one-to-many matching time for biometric recognition, resulting in a faster biometric authentication mechanism.
Privacy-leakage codes for biometric authentication systems

NARCIS (Netherlands)

Ignatenko, T.; Willems, F.M.J.

2014-01-01

In biometric privacy-preserving authentication systems that are based on key-binding, two terminals observe two correlated biometric sequences. The first terminal selects a secret key, which is independent of the biometric data, binds this secret key to the observed biometric sequence and
Biometric Systems Private by Design: Reasoning about privacy properties of biometric system architectures

OpenAIRE

Bringer, Julien; Chabanne, Herve; Metayer, Daniel Le; Lescuyer, Roch

2017-01-01

This work aims to show the applicability, and how, of privacy by design approach to biometric systems and the benefit of using formal methods to this end. Starting from a general framework that has been introduced at STM in 2014, that enables to define privacy architectures and to formally reason about their properties, we explain how it can be adapted to biometrics. The choice of particular techniques and the role of the components (central server, secure module, biometric terminal, smart ca...
The use of biometrics in IT

OpenAIRE

Bílý, Petr

2009-01-01

Biometrics is increasingly applied in IT (biometric methods today generally use computer technology), mostly used to authenticate users. The aim of this thesis is to describe and compare two selected biometric methods. These methods are fingerprints and scanning of human face. The contribution of this work is to provide information on biometric identification methods, their advantages and disadvantages, and deployment options. If an organization decides to strengthen their security systems wi...
Measuring Biometric Sample Quality in terms of Biometric Feature Information in Iris Images

Directory of Open Access Journals (Sweden)

R. Youmaran

2012-01-01

Full Text Available This paper develops an approach to measure the information content in a biometric feature representation of iris images. In this context, the biometric feature information is calculated using the relative entropy between the intraclass and interclass feature distributions. The collected data is regularized using a Gaussian model of the feature covariances in order to practically measure the biometric information with limited data samples. An example of this method is shown for iris templates processed using Principal-Component Analysis- (PCA- and Independent-Component Analysis- (ICA- based feature decomposition schemes. From this, the biometric feature information is calculated to be approximately 278 bits for PCA and 288 bits for ICA iris features using Masek's iris recognition scheme. This value approximately matches previous estimates of iris information content.
An Efficient Human Identification through MultiModal Biometric System

Directory of Open Access Journals (Sweden)

K. Meena

Full Text Available ABSTRACT Human identification is essential for proper functioning of society. Human identification through multimodal biometrics is becoming an emerging trend, and one of the reasons is to improve recognition accuracy. Unimodal biometric systems are affected by various problemssuch as noisy sensor data,non-universality, lack of individuality, lack of invariant representation and susceptibility to circumvention.A unimodal system has limited accuracy. Hence, Multimodal biometric systems by combining more than one biometric feature in different levels are proposed in order to enhance the performance of the system. A supervisor module combines the different opinions or decisions delivered by each subsystem and then make a final decision. In this paper, a multimodal biometrics authentication is proposed by combining face, iris and finger features. Biometric features are extracted by Local Derivative Ternary Pattern (LDTP in Contourlet domain and an extensive evaluation of LDTP is done using Support Vector Machine and Nearest Neighborhood Classifier. The experimental evaluations are performed on a public dataset demonstrating the accuracy of the proposed system compared with the existing systems. It is observed that, the combination of face, fingerprint and iris gives better performance in terms of accuracy, False Acceptance Rate, False Rejection Rate with minimum computation time.
Biometric Features in Person Recognition Systems

Directory of Open Access Journals (Sweden)

Edgaras Ivanovas

2011-03-01

Full Text Available Lately a lot of research effort is devoted for recognition of a human being using his biometric characteristics. Biometric recognition systems are used in various applications, e. g., identification for state border crossing or firearm, which allows only enrolled persons to use it. In this paper biometric characteristics and their properties are reviewed. Development of high accuracy system requires distinctive and permanent characteristics, whereas development of user friendly system requires collectable and acceptable characteristics. It is showed that properties of biometric characteristics do not influence research effort significantly. Properties of biometric characteristic features and their influence are discussed.Article in Lithuanian
Recent Self-Reported Cannabis Use Is Associated With the Biometrics of Delta-9-Tetrahydrocannabinol.

Science.gov (United States)

Smith, Matthew J; Alden, Eva C; Herrold, Amy A; Roberts, Andrea; Stern, Dan; Jones, Joseph; Barnes, Allan; O'Connor, Kailyn P; Huestis, Marilyn A; Breiter, Hans C

2018-05-01

Research typically characterizes cannabis use by self-report of cannabis intake frequency. In an effort to better understand relationships between measures of cannabis use, we evaluated if Δ-9-tetrahydrocannabinol (THC) and metabolite concentrations (biometrics) were associated with a calibrated timeline followback (TLFB) assessment of cannabis use. Participants were 35 young adult male cannabis users who completed a calibrated TLFB measure of cannabis use over the past 30 days, including time of last use. The calibration required participants handling four plastic bags of a cannabis substitute (0.25, 0.5, 1.0, and 3.5 grams) to quantify cannabis consumed. Participants provided blood and urine samples for analysis of THC and metabolites, at two independent laboratories. Participants abstained from cannabis use on the day of sample collection. We tested Pearson correlations between the calibrated TLFB measures and cannabis biometrics. Strong correlations were seen between urine and blood biometrics (all r > .73, all p biometric, including urine 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (THCCOOH) and blood THC, 11-hydroxy-THC (11-OH-THC), THCCOOH, THCCOOH-glucuronide (times of use: r > .48-.61, all p .40-.49, all p biometrics. The calibration of cannabis intake in grams was associated with each biometric, although the simple TLFB measure of times of use produced the strongest relationships with all five biometrics. These findings suggest that combined self-report and biometric data together convey the complexity of cannabis use, but allow that either the use of calibrated TLFB measures or biometrics may be sufficient for assessment of cannabis use in research.
Securing Biometric Images using Reversible Watermarking

OpenAIRE

Thampi, Sabu M.; Jacob, Ann Jisma

2011-01-01

Biometric security is a fast growing area. Protecting biometric data is very important since it can be misused by attackers. In order to increase security of biometric data there are different methods in which watermarking is widely accepted. A more acceptable, new important development in this area is reversible watermarking in which the original image can be completely restored and the watermark can be retrieved. But reversible watermarking in biometrics is an understudied area. Reversible ...
Performance Evaluation Of Behavioral Biometric Systems

OpenAIRE

Cherifi , Fouad; Hemery , Baptiste; Giot , Romain; Pasquet , Marc; Rosenberger , Christophe

2009-01-01

We present in this chapter an overview of techniques for the performance evaluation of behavioral biometric systems. The BioAPI standard that defines the architecture of a biometric system is presented in the first part of the chapter... The general methodology for the evaluation of biometric systems is given including statistical metrics, definition of benchmark databases and subjective evaluation. These considerations rely with the ISO/IEC19795-1 standard describing the biometric performanc...
Modular Biometric Monitoring System

Science.gov (United States)

Chmiel, Alan J. (Inventor); Humphreys, Bradley T. (Inventor)

2017-01-01

A modular system for acquiring biometric data includes a plurality of data acquisition modules configured to sample biometric data from at least one respective input channel at a data acquisition rate. A representation of the sampled biometric data is stored in memory of each of the plurality of data acquisition modules. A central control system is in communication with each of the plurality of data acquisition modules through a bus. The central control system is configured to control communication of data, via the bus, with each of the plurality of data acquisition modules.
Privacy-Preserving Biometric Authentication: Challenges and Directions

Directory of Open Access Journals (Sweden)

Elena Pagnin

2017-01-01

Full Text Available An emerging direction for authenticating people is the adoption of biometric authentication systems. Biometric credentials are becoming increasingly popular as a means of authenticating people due to the wide range of advantages that they provide with respect to classical authentication methods (e.g., password-based authentication. The most characteristic feature of this authentication method is the naturally strong bond between a user and her biometric credentials. This very same advantageous property, however, raises serious security and privacy concerns in case the biometric trait gets compromised. In this article, we present the most challenging issues that need to be taken into consideration when designing secure and privacy-preserving biometric authentication protocols. More precisely, we describe the main threats against privacy-preserving biometric authentication systems and give directions on possible countermeasures in order to design secure and privacy-preserving biometric authentication protocols.
Encryption Technology based on Human Biometrics

Directory of Open Access Journals (Sweden)

Wei Yang

2017-08-01

Full Text Available The research progress of encryption technologies based on human biometrics is reviewed in this paper.The technologies that utilize human biometrics to make information encryption and identity authentication,and the technologies which combine biometrics encryption with optical encryption methods are introduced in detail.The advantages and disadvantages of these encryption systems are discussed,and the obstacles in practical applications are pointed out.Finally,the prospect of the new encryption technologies that are based on human biometrics are predicted.

Environmental Testing Methodology in Biometrics

OpenAIRE

Fernández Saavedra, Belén; Sánchez Reíllo, Raúl; Alonso Moreno, Raúl; Miguel Hurtado, Óscar

2010-01-01

8 pages document + 5-slide presentation.-- Contributed to: 1st International Biometric Performance Conference (IBPC 2010, NIST, Gaithersburg, MD, US, Mar 1-5, 2010). Recently, biometrics is used in many security systems and these systems can be located in different environments. As many experts claim and previous works have demonstrated, environmental conditions influence biometric performance. Nevertheless, there is not a specific methodology for testing this influence at the moment...
3D biometrics systems and applications

CERN Document Server

Zhang, David

2013-01-01

Includes discussions on popular 3D imaging technologies, combines them with biometric applications, and then presents real 3D biometric systems Introduces many efficient 3D feature extraction, matching, and fusion algorithms Techniques presented have been supported by experimental results using various 3D biometric classifications
Iris and periocular biometrics

CERN Document Server

Rathgeb, Christian

2017-01-01

This book provides an overview of scientific fundamentals and principles of iris and periocular biometric recognition. It covers: an introduction to iris and periocular recognition; a selective overview of issues and challenges; soft biometric classification; security aspects; privacy protection and forensics; and future trends.
Evolutionary Algorithms Application Analysis in Biometric Systems

OpenAIRE

N. Goranin; A. Cenys

2010-01-01

Wide usage of biometric information for person identity verification purposes, terrorist acts prevention measures and authenticationprocess simplification in computer systems has raised significant attention to reliability and efficiency of biometricsystems. Modern biometric systems still face many reliability and efficiency related issues such as reference databasesearch speed, errors while recognizing of biometric information or automating biometric feature extraction. Current scientificinv...
Secure authentication system that generates seed from biometric information.

Science.gov (United States)

Kim, Yeojin; Ahn, Jung-Ho; Byun, Hyeran

2005-02-10

As biometric recognition techniques are gradually improved, the stability of biometric authentication systems are enhanced. Although bioinformation has properties that make it resistant to fraud, biometric authentication systems are not immune to hacking. We show a secure biometric authentication system (1) to guarantee the integrity of biometric information by mixing data by use of a biometric key and (2) to raise recognition rates by use of bimodal biometrics.
BossPro: a biometrics-based obfuscation scheme for software protection

Science.gov (United States)

Kuseler, Torben; Lami, Ihsan A.; Al-Assam, Hisham

2013-05-01

This paper proposes to integrate biometric-based key generation into an obfuscated interpretation algorithm to protect authentication application software from illegitimate use or reverse-engineering. This is especially necessary for mCommerce because application programmes on mobile devices, such as Smartphones and Tablet-PCs are typically open for misuse by hackers. Therefore, the scheme proposed in this paper ensures that a correct interpretation / execution of the obfuscated program code of the authentication application requires a valid biometric generated key of the actual person to be authenticated, in real-time. Without this key, the real semantics of the program cannot be understood by an attacker even if he/she gains access to this application code. Furthermore, the security provided by this scheme can be a vital aspect in protecting any application running on mobile devices that are increasingly used to perform business/financial or other security related applications, but are easily lost or stolen. The scheme starts by creating a personalised copy of any application based on the biometric key generated during an enrolment process with the authenticator as well as a nuance created at the time of communication between the client and the authenticator. The obfuscated code is then shipped to the client's mobile devise and integrated with real-time biometric extracted data of the client to form the unlocking key during execution. The novelty of this scheme is achieved by the close binding of this application program to the biometric key of the client, thus making this application unusable for others. Trials and experimental results on biometric key generation, based on client's faces, and an implemented scheme prototype, based on the Android emulator, prove the concept and novelty of this proposed scheme.
NIST biometric evaluations and developments

Science.gov (United States)

Garris, Michael D.; Wilson, Charles L.

2005-05-01

This paper presents an R&D framework used by the National Institute of Standards and Technology (NIST) for biometric technology testing and evaluation. The focus of this paper is on fingerprint-based verification and identification. Since 9-11 the NIST Image Group has been mandated by Congress to run a program for biometric technology assessment and biometric systems certification. Four essential areas of activity are discussed: 1) developing test datasets, 2) conducting performance assessment; 3) technology development; and 4) standards participation. A description of activities and accomplishments are provided for each of these areas. In the process, methods of performance testing are described and results from specific biometric technology evaluations are presented. This framework is anticipated to have broad applicability to other technology and application domains.
Simplified Multimodal Biometric Identification

Directory of Open Access Journals (Sweden)

Abhijit Shete

2014-03-01

Full Text Available Multibiometric systems are expected to be more reliable than unimodal biometric systems for personal identification due to the presence of multiple, fairly independent pieces of evidence e.g. Unique Identification Project "Aadhaar" of Government of India. In this paper, we present a novel wavelet based technique to perform fusion at the feature level and score level by considering two biometric modalities, face and fingerprint. The results indicate that the proposed technique can lead to substantial improvement in multimodal matching performance. The proposed technique is simple because of no preprocessing of raw biometric traits as well as no feature and score normalization.
Impact of environmental factors on biometric matching during human decomposition

Energy Technology Data Exchange (ETDEWEB)

Bolme, David S [ORNL; Tokola, Ryan A [ORNL; Boehnen, Chris Bensing [ORNL; Saul, Tiffany B [ORNL; Sauerwein, Kelly A [ORNL; Steadman, Dawnie W [ORNL

2016-01-01

Automatic recognition systems are a valuable tool for identifying unknown deceased individuals. Immediately af- ter death fingerprint and face biometric samples are easy to collect using standard sensors and cameras and can be easily matched to anti-mortem biometric samples. Even though post-mortem fingerprints and faces have been used for decades, there are no studies that track these biomet- rics through the later stages of decomposition to determine the length of time the biometrics remain viable. This paper discusses a multimodal dataset of fingerprints, faces, and irises from 14 human cadavers that decomposed outdoors under natural conditions. Results include predictive models relating time and temperature, measured as Accumulated Degree Days (ADD), and season (winter, spring, summer) to the predicted probably of automatic verification using a commercial algorithm.
GPS Position Time Series @ JPL

Science.gov (United States)

Owen, Susan; Moore, Angelyn; Kedar, Sharon; Liu, Zhen; Webb, Frank; Heflin, Mike; Desai, Shailen

2013-01-01

Different flavors of GPS time series analysis at JPL - Use same GPS Precise Point Positioning Analysis raw time series - Variations in time series analysis/post-processing driven by different users. center dot JPL Global Time Series/Velocities - researchers studying reference frame, combining with VLBI/SLR/DORIS center dot JPL/SOPAC Combined Time Series/Velocities - crustal deformation for tectonic, volcanic, ground water studies center dot ARIA Time Series/Coseismic Data Products - Hazard monitoring and response focused center dot ARIA data system designed to integrate GPS and InSAR - GPS tropospheric delay used for correcting InSAR - Caltech's GIANT time series analysis uses GPS to correct orbital errors in InSAR - Zhen Liu's talking tomorrow on InSAR Time Series analysis
Multi-biometrics based cryptographic key regeneration scheme

OpenAIRE

Kanade , Sanjay Ganesh; Petrovska-Delacrétaz , Dijana; Dorizzi , Bernadette

2009-01-01

International audience; Biometrics lack revocability and privacy while cryptography cannot detect the user's identity. By obtaining cryptographic keys using biometrics, one can achieve the properties such as revocability, assurance about user's identity, and privacy. In this paper, we propose a multi-biometric based cryptographic key regeneration scheme. Since left and right irises of a person are uncorrelated, we treat them as two independent biometrics and combine in our system. We propose ...
Improvement of security techniques and protection of biometric data in biometric systems: Presentation of International Standard ISO 24745

OpenAIRE

Milinković, Milorad

2017-01-01

This paper presents the International Standard ISO 24745 as a potential security tool for biometric information protection, more precisely as a tool for privacy protection in biometric systems. This is one of the latest internationally accepted standards that address the security issues of biometric systems.
Comparative analysis of the quality of biometric methods

OpenAIRE

Filipčík, Jan

2010-01-01

The main objective is to describe and analyze the types of biometric identification and selected biometric methods and identify their strengths and weaknesses compared to the current document type of identification and verification of persons and compared to other biometric methods and then focus on the relationships and support of biometric methods in terms of IS / ICT services. The work will consist of 5 types of biometric methods namely dactyloscopy, hand geometry scanning, facial scanning...
Bridging the gap: from biometrics to forensics.

Science.gov (United States)

Jain, Anil K; Ross, Arun

2015-08-05

Biometric recognition, or simply biometrics, refers to automated recognition of individuals based on their behavioural and biological characteristics. The success of fingerprints in forensic science and law enforcement applications, coupled with growing concerns related to border control, financial fraud and cyber security, has generated a huge interest in using fingerprints, as well as other biological traits, for automated person recognition. It is, therefore, not surprising to see biometrics permeating various segments of our society. Applications include smartphone security, mobile payment, border crossing, national civil registry and access to restricted facilities. Despite these successful deployments in various fields, there are several existing challenges and new opportunities for person recognition using biometrics. In particular, when biometric data is acquired in an unconstrained environment or if the subject is uncooperative, the quality of the ensuing biometric data may not be amenable for automated person recognition. This is particularly true in crime-scene investigations, where the biological evidence gleaned from a scene may be of poor quality. In this article, we first discuss how biometrics evolved from forensic science and how its focus is shifting back to its origin in order to address some challenging problems. Next, we enumerate the similarities and differences between biometrics and forensics. We then present some applications where the principles of biometrics are being successfully leveraged into forensics in order to solve critical problems in the law enforcement domain. Finally, we discuss new collaborative opportunities for researchers in biometrics and forensics, in order to address hitherto unsolved problems that can benefit society at large. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
Using Biometric Characteristics to Increase ITS Security

Directory of Open Access Journals (Sweden)

Miroslav Bača

2007-11-01

Full Text Available Terrorist attacks in New York City and Washington, Districtof Columbia on the morning of September 11, 2001 havechanged our lives. The secwity problem became very importantregarding all spheres of human activities. Tracking persons(employees, customers etc. in ITS (Intelligent Transport Systemis a huge problem. Biometrics offers a very good solutionfor this problem and is today maybe one of the most promisingtechniques for person's secure verification and authentication;biometric system also features some advantages when comparedto other security systems. When using a biometric systemone has to be careful because the functionality of a biometricapplication can be dramatically aggravated if inappropriatebiometric features are selected. Classification of biometric featureson contact and contactless, or distinction between"strong" and "soft" biometric features gives a framework for usingbiometric features, but it does not ensure that biometric featŁtres are implemented at a satisfactory level. The usage ofmultimodal or unimodal biometric system can significantly increasethe system security but it also opens plenty of questionslike privacy etc. This paper describes the implementation ofbiometric features which can be used in ITS, and delineates anew model of usage.
Embedded System for Biometric Identification

OpenAIRE

Rosli, Ahmad Nasir Che

2010-01-01

This chapter describes the design and implementation of an Embedded System for Biometric Identification from hardware and software perspectives. The first part of the chapter describes the idea of biometric identification. This includes the definition of
Time series analysis time series analysis methods and applications

CERN Document Server

Rao, Tata Subba; Rao, C R

2012-01-01

The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments. The Handbook of Statistics is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with Volume 30 dealing with time series. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriented techniques, with the applied statistician in mind as the primary audience. Comprehensively presents the various aspects of statistical methodology Discusses a wide variety of diverse applications and recent developments Contributors are internationally renowened experts in their respect...
Highly comparative time-series analysis: the empirical structure of time series and their methods.

Science.gov (United States)

Fulcher, Ben D; Little, Max A; Jones, Nick S

2013-06-06

The process of collecting and organizing sets of observations represents a common theme throughout the history of science. However, despite the ubiquity of scientists measuring, recording and analysing the dynamics of different processes, an extensive organization of scientific time-series data and analysis methods has never been performed. Addressing this, annotated collections of over 35 000 real-world and model-generated time series, and over 9000 time-series analysis algorithms are analysed in this work. We introduce reduced representations of both time series, in terms of their properties measured by diverse scientific methods, and of time-series analysis methods, in terms of their behaviour on empirical time series, and use them to organize these interdisciplinary resources. This new approach to comparing across diverse scientific data and methods allows us to organize time-series datasets automatically according to their properties, retrieve alternatives to particular analysis methods developed in other scientific disciplines and automate the selection of useful methods for time-series classification and regression tasks. The broad scientific utility of these tools is demonstrated on datasets of electroencephalograms, self-affine time series, heartbeat intervals, speech signals and others, in each case contributing novel analysis techniques to the existing literature. Highly comparative techniques that compare across an interdisciplinary literature can thus be used to guide more focused research in time-series analysis for applications across the scientific disciplines.
The relation between the secrecy rate of biometric template protection and biometric recognition performance

NARCIS (Netherlands)

Veldhuis, Raymond N.J.

2015-01-01

A theoretical result relating the maximum achievable security of the family of biometric template protection systems known as key-binding systems to the recognition performance of a biometric recognition system that is optimal in Neyman-Pearson sense is derived. The relation allows for the
A novel approach to transformed biometrics using successive projections

Science.gov (United States)

Gopi, E. S.

2010-02-01

Unlike user created password, number of biometrics is limited for creating account in different organizations. Transformed biometrics attempts to solve the problem by transforming the biometric into another form, which is unique to the particular organization. This makes the availability of different transformed biometrics in different organizations transformed from the same biometrics and helps in foolproof transactions. In this article a novel approach to transformed biometrics using successive projection technique is suggested .In the proposed technique, the user can register up to 5*4n-1 organizations if the length of the biometric password is 'n'.

Biometrics and their use in e-passports

NARCIS (Netherlands)

Schouten, B.A.M.; Jacobs, B.P.F.

2009-01-01

A successful design, deployment and operation of biometric systems depends highly on the results for existing biometrical technologies and components. These existing technologies as well as new solutions need to be evaluated on their performance. However it is often forgotten that the biometric
Biometrics and their use in e-passports

NARCIS (Netherlands)

Prof. Bart Jacobs; B.A.M. Ben Schouten

2007-01-01

A succesful design, deployment and operation of biometric systems depends highly on the results for existing biometrical technologies and components. These existing technologies as well as new solutions need to be evaluated on their performance. However it is often forgotten that the biometric
Biometric security from an information-theoretical perspective

NARCIS (Netherlands)

Ignatenko, T.; Willems, F.M.J.

2012-01-01

In this review, biometric systems are studied from an information theoretical point of view. In the first part biometric authentication systems are studied. The objective of these systems is, observing correlated enrollment and authentication biometric sequences, to generate or convey as large as
Biometric and intelligent decision making support

CERN Document Server

Kaklauskas, Arturas

2015-01-01

This book presents different methods for analyzing the body language (movement, position, use of personal space, silences, pauses and tone, the eyes, pupil dilation or constriction, smiles, body temperature and the like) for better understanding people’s needs and actions, including biometric data gathering and reading. Different studies described in this book indicate that sufficiently much data, information and knowledge can be gained by utilizing biometric technologies. This is the first, wide-ranging book that is devoted completely to the area of intelligent decision support systems, biometrics technologies and their integrations. This book is designated for scholars, practitioners and doctoral and master’s degree students in various areas and those who are interested in the latest biometric and intelligent decision making support problems and means for their resolutions, biometric and intelligent decision making support systems and the theory and practice of their integration and the opportunities fo...
BIOMETRIC IDENTITY VERIFICATION IN HEALTH SERVICES: A BIOMETRIC SURVEILLANCE PRACTICE IN TURKEY

OpenAIRE

İlker ŞİRİN

2014-01-01

Determination or verification of identity with biometric methods has a widespread use especially at borders for security reasons. Social Security Institution transferred the biometric identity verification practice to health sercives that are provided by private and university hospitals. The risks of the new system considering the privacy of personal data are under debate. Although there are announcements or manuals of Social Security Institution regarding the implementation...
A Survey On Biometric Security Technologies From Cloud Computing Perspective

Directory of Open Access Journals (Sweden)

Shivashish Ratnam

2015-08-01

Full Text Available Cloud computing is one of the rising technologies that takes set of connections users to the next level. Cloud is a technology where resources are paid as per usage rather than owned. One of the major challenges in this technology is Security. Biometric systems provide the answer to ensure that the rendered services are accessed only by a legal user or an authorized user and no one else. Biometric systems recognize users based on behavioral or physiological characteristics. The advantages of such systems over traditional validation methods such as passwords and IDs are well known and hence biometric systems are progressively gaining ground in terms of usage. This paper brings about a new replica of a security system where in users have to offer multiple biometric finger prints during Enrollment for a service. These templates are stored at the cloud providers section. The users are authenticated based on these finger print designed templates which have to be provided in the order of arbitrary numbers or imaginary numbers that are generated every time continuously. Both finger prints templates and images are present and they provided every time duration are encrypted or modified for enhanced security.
An efficient visualization method for analyzing biometric data

Science.gov (United States)

Rahmes, Mark; McGonagle, Mike; Yates, J. Harlan; Henning, Ronda; Hackett, Jay

2013-05-01

We introduce a novel application for biometric data analysis. This technology can be used as part of a unique and systematic approach designed to augment existing processing chains. Our system provides image quality control and analysis capabilities. We show how analysis and efficient visualization are used as part of an automated process. The goal of this system is to provide a unified platform for the analysis of biometric images that reduce manual effort and increase the likelihood of a match being brought to an examiner's attention from either a manual or lights-out application. We discuss the functionality of FeatureSCOPE™ which provides an efficient tool for feature analysis and quality control of biometric extracted features. Biometric databases must be checked for accuracy for a large volume of data attributes. Our solution accelerates review of features by a factor of up to 100 times. Review of qualitative results and cost reduction is shown by using efficient parallel visual review for quality control. Our process automatically sorts and filters features for examination, and packs these into a condensed view. An analyst can then rapidly page through screens of features and flag and annotate outliers as necessary.
Avoiding terminological confusion between the notions of 'biometrics' and 'biometric data' : An investigation into the meanings of the terms from a European data protection and a scientific perspective

NARCIS (Netherlands)

Jasserand, Catherine

2015-01-01

This article has been motivated by an observation: the lack of rigor by European bodies when they use scientific terms to address data protection and privacy issues raised by biometric technologies and biometric data. In particular, they improperly use the term ‘biometrics’ to mean at the same time
Physiological Biometric Authentication Systems Advantages Disadvantages And Future Development A Review

Directory of Open Access Journals (Sweden)

Israa M. Alsaadi

2015-08-01

Full Text Available Abstract With the fast increasing of the electronic crimes and their related issues deploying a reliable user authentication system became a significant task for both of access control and securing users private data. Human biometric characteristics such as face finger iris scanning voice signature and other features provide a dependable security level for both of the personal and the public use. Many biometric authentication systems have been approached for long time. Due to the uniqueness of human biometrics witch played a master role in degrading imposters attacks. Such authentication models have overcome other traditional security methods like passwords and PIN. This paper aims to briefly address the psychological biometric authentication techniques. Also a brief summary to the advantages disadvantages and future developments of each method is provided in this paper.
Recommendation on the Use of Biometric Technology

DEFF Research Database (Denmark)

Juul, Niels Christian

2013-01-01

Biometric technology is based on the use of information linked to individuals. Hence, privacy and security in biometric applications becomes a concern and the need to assess such applications thoroughly becomes equally important. Guidelines for application of biometric technology must ensure...... a positive impact on both security and privacy. Based on two cases of biometric application, which have been assessed by the Danish Data Protecting Agency, this chapter present a set of recommendations to legislators, regulators, corporations and individuals on the appropriate use of biometric technologies...... put forward by the Danish Board of Technology. The recommendations are discussed and compared to the similar proposal put forward by the European Article 29 Data Protection Working Party....
Introduction to Time Series Modeling

CERN Document Server

Kitagawa, Genshiro

2010-01-01

In time series modeling, the behavior of a certain phenomenon is expressed in relation to the past values of itself and other covariates. Since many important phenomena in statistical analysis are actually time series and the identification of conditional distribution of the phenomenon is an essential part of the statistical modeling, it is very important and useful to learn fundamental methods of time series modeling. Illustrating how to build models for time series using basic methods, "Introduction to Time Series Modeling" covers numerous time series models and the various tools f
Soft Biometrics; Human Identification Using Comparative Descriptions.

Science.gov (United States)

Reid, Daniel A; Nixon, Mark S; Stevenage, Sarah V

2014-06-01

Soft biometrics are a new form of biometric identification which use physical or behavioral traits that can be naturally described by humans. Unlike other biometric approaches, this allows identification based solely on verbal descriptions, bridging the semantic gap between biometrics and human description. To permit soft biometric identification the description must be accurate, yet conventional human descriptions comprising of absolute labels and estimations are often unreliable. A novel method of obtaining human descriptions will be introduced which utilizes comparative categorical labels to describe differences between subjects. This innovative approach has been shown to address many problems associated with absolute categorical labels-most critically, the descriptions contain more objective information and have increased discriminatory capabilities. Relative measurements of the subjects' traits can be inferred from comparative human descriptions using the Elo rating system. The resulting soft biometric signatures have been demonstrated to be robust and allow accurate recognition of subjects. Relative measurements can also be obtained from other forms of human representation. This is demonstrated using a support vector machine to determine relative measurements from gait biometric signatures-allowing retrieval of subjects from video footage by using human comparisons, bridging the semantic gap.
On the Design of Forgiving Biometric Security Systems

Science.gov (United States)

Phan, Raphael C.-W.; Whitley, John N.; Parish, David J.

This work aims to highlight the fundamental issue surrounding biometric security systems: it’s all very nice until a biometric is forged, but what do we do after that? Granted, biometric systems are by physical nature supposedly much harder to forge than other factors of authentication since biometrics on a human body are by right unique to the particular human person. Yet it is also due to this physical nature that makes it much more catastrophic when a forgery does occur, because it implies that this uniqueness has been forged as well, threatening the human individuality; and since crime has by convention relied on identifying suspects by biometric characteristics, loss of this biometric uniqueness has devastating consequences on the freedom and basic human rights of the victimized individual. This uniqueness forgery implication also raises the motivation on the adversary to forge since a successful forgery leads to much more impersonation situations when biometric systems are used i.e. physical presence at crime scenes, identification and access to security systems and premises, access to financial accounts and hence the ability to use the victim’s finances. Depending on the gains, a desperate highly motivated adversary may even resort to directly obtaining the victim’s biometric parts by force e.g. severing the parts from the victim’s body; this poses a risk and threat not just to the individual’s uniqueness claim but also to personal safety and well being. One may then wonder if it is worth putting one’s assets, property and safety into the hands of biometrics based systems when the consequences of biometric forgery far outweigh the consequences of system compromises when no biometrics are used.
Biometrics Enabling Capability Increment 1 (BEC Inc 1)

Science.gov (United States)

2016-03-01

modal biometrics submissions to include iris, face, palm and finger prints from biometrics collection devices, which will support the Warfighter in...2016 Major Automated Information System Annual Report Biometrics Enabling Capability Increment 1 (BEC Inc 1) Defense Acquisition Management...Phone: 227-3119 DSN Fax: Date Assigned: July 15, 2015 Program Information Program Name Biometrics Enabling Capability Increment 1 (BEC Inc 1) DoD
BIOMETRIC SECURITY: ALTERNATIF PENGENDALIAN DALAM SISTEM INFORMASI AKUNTANSI TERKOMPUTERISASI

Directory of Open Access Journals (Sweden)

Josua Tarigan

2004-01-01

Full Text Available As organization search more secure authentication method for user access, biometric security technology is gaining more and more attention. The implementation of biometric security technology in accounting information systems was physical access, virtual access, e-commerce applications and covert suveillance. There are three phase when an organization implementation biometric technology: strategic planning and budgeting, developing a system reliability plan and documentation. The challenges will face when develop biometric technology as control in accounting information system are standardization, hybrid technology uses, life cycle management. Abstract in Bahasa Indonesia : Adanya keinginan setiap organisasi untuk mencari metode pengamanan authentication yang lebih untuk akses user, dijawab dengan adanya teknologi biometric security yang mendapat perhatian yang cukup besar bagi organisasi. Implementasi teknologi biometric security cukup luas dalam sistem informasi akuntansi yaitu sebagai pengendalian pada physical access, virtual access, e-commerce applications dan covert surveillance. Dalam mengimplementasikan teknologi biometric, ada tiga tahapan yang harus dilakukan organisasi, yakni strategic planning and budgeting, developing a system reliability plan dan documentation. Tantangan yang akan dihadapi dalam mengembangkan teknologi biometric sebagai pengendalian dalam sistem informasi akuntansi yakni standarisasi, aplikasi teknologi hybrid dan manajemen siklus hidup pada biometric security. Kata kunci: authentication, akses user dan biometric security.
Transfer learning for bimodal biometrics recognition

Science.gov (United States)

Dan, Zhiping; Sun, Shuifa; Chen, Yanfei; Gan, Haitao

2013-10-01

Biometrics recognition aims to identify and predict new personal identities based on their existing knowledge. As the use of multiple biometric traits of the individual may enables more information to be used for recognition, it has been proved that multi-biometrics can produce higher accuracy than single biometrics. However, a common problem with traditional machine learning is that the training and test data should be in the same feature space, and have the same underlying distribution. If the distributions and features are different between training and future data, the model performance often drops. In this paper, we propose a transfer learning method for face recognition on bimodal biometrics. The training and test samples of bimodal biometric images are composed of the visible light face images and the infrared face images. Our algorithm transfers the knowledge across feature spaces, relaxing the assumption of same feature space as well as same underlying distribution by automatically learning a mapping between two different but somewhat similar face images. According to the experiments in the face images, the results show that the accuracy of face recognition has been greatly improved by the proposed method compared with the other previous methods. It demonstrates the effectiveness and robustness of our method.
Atlantic Bluefin Tuna (Thunnus thynnus) Biometrics and Condition.

Science.gov (United States)

Rodriguez-Marin, Enrique; Ortiz, Mauricio; Ortiz de Urbina, José María; Quelle, Pablo; Walter, John; Abid, Noureddine; Addis, Piero; Alot, Enrique; Andrushchenko, Irene; Deguara, Simeon; Di Natale, Antonio; Gatt, Mark; Golet, Walter; Karakulak, Saadet; Kimoto, Ai; Macias, David; Saber, Samar; Santos, Miguel Neves; Zarrad, Rafik

2015-01-01

The compiled data for this study represents the first Atlantic and Mediterranean-wide effort to pool all available biometric data for Atlantic bluefin tuna (Thunnus thynnus) with the collaboration of many countries and scientific groups. Biometric relationships were based on an extensive sampling (over 140,000 fish sampled), covering most of the fishing areas for this species in the North Atlantic Ocean and Mediterranean Sea. Sensitivity analyses were carried out to evaluate the representativeness of sampling and explore the most adequate procedure to fit the weight-length relationship (WLR). The selected model for the WLRs by stock included standardized data series (common measurement types) weighted by the inverse variability. There was little difference between annual stock-specific round weight-straight fork length relationships, with an overall difference of 6% in weight. The predicted weight by month was estimated as an additional component in the exponent of the weight-length function. The analyses of monthly variations of fish condition by stock, maturity state and geographic area reflect annual cycles of spawning and feeding behavior. We update and improve upon the biometric relationships for bluefin currently used by the International Commission for the Conservation of Atlantic Tunas, by incorporating substantially larger datasets than ever previously compiled, providing complete documentation of sources and employing robust statistical fitting. WLRs and other conversion factors estimated in this study differ from the ones used in previous bluefin stock assessments.
Voice Biometrics as a Way to Self-service Password Reset

Science.gov (United States)

Hohgräfe, Bernd; Jacobi, Sebastian

Password resets are time consuming. Especially when urgent jobs need to be done, it is cumbersome to inform the user helpdesk, to identify oneself and then to wait for response. It is easy to enter a wrong password multiple times, which leads to the blocking of the application. Voice biometrics is an easy and secure way for individuals to reset their own password. Read more about how you can ease the burden of your user helpdesk and how voice biometric password resets benefit your expense situation without harming your security.
Biometric Score Calibration for Forensic Face Recognition

NARCIS (Netherlands)

Ali, Tauseef

2014-01-01

When two biometric specimens are compared using an automatic biometric recognition system, a similarity metric called “score‿ can be computed. In forensics, one of the biometric specimens is from an unknown source, for example, from a CCTV footage or a fingermark found at a crime scene and the other
Biometric parameters of the bream (Abramis brama) as indicators for long-term changes in fish health and environmental quality--data from the German ESB.

Science.gov (United States)

Teubner, Diana; Paulus, Martin; Veith, Michael; Klein, Roland

2015-02-01

Piscifaunal health depends upon the state and quality of the aquatic environment. Variations in physical condition of fish may therefore be attributed to changes in environmental quality. Based on time series of up to 20 years of biometric data of bream from multiple sampling sites of the German environmental specimen bank (ESB), this study assessed whether changes in biometric parameters are able to indicate long-term alterations in fish health and environmental quality. Evaluated biometric parameters of fish health comprised length and weight of individuals of a defined age class, the condition factor, lipid content and hepatosomatic index (HSI). Although there are negative trends of the HSI, the overall development of health parameters can be interpreted as positive. This seems to suggest that health parameters conclusively mirror the long-term improvement of water quality in the selected rivers. However, the applicability of the condition factor as well as lipid content as indicators for fish health remained subject to restrictions. Altogether, the results from the ESB confirmed the high value of biometric parameters for monitoring of long-term changes in state and quality of aquatic ecosystems.

3D Biometrics for Hindfoot Alignment Using Weightbearing CT.

Science.gov (United States)

Lintz, François; Welck, Matthew; Bernasconi, Alessio; Thornton, James; Cullen, Nicholas P; Singh, Dishan; Goldberg, Andy

2017-06-01

Hindfoot alignment on 2D radiographs can present anatomical and operator-related bias. In this study, software designed for weightbearing computed tomography (WBCT) was used to calculate a new 3D biometric tool: the Foot and Ankle Offset (FAO). We described the distribution of FAO in a series of data sets from clinically normal, varus, and valgus cases, hypothesizing that FAO values would be significantly different in the 3 groups. In this retrospective cohort study, 135 data sets (57 normal, 38 varus, 40 valgus) from WBCT (PedCAT; CurveBeam LLC, Warrington, PA) were obtained from a specialized foot and ankle unit. 3D coordinates of specific anatomical landmarks (weightbearing points of the calcaneus, of the first and fifth metatarsal heads and the highest and centermost point on the talar dome) were collected. These data were processed with the TALAS system (CurveBeam), which resulted in an FAO value for each case. Intraobserver and interobserver reliability were also assessed. In normal cases, the mean value for FAO was 2.3% ± 2.9%, whereas in varus and valgus cases, the mean was -11.6% ± 6.9% and 11.4% ± 5.7%, respectively, with a statistically significant difference among groups ( P biometrics. The present study introduces the concept of 3D biometrics and describes an efficient, semiautomatic tool for measuring hindfoot alignment. Level III, retrospective comparative study.
The Effect of Decomposition on the Efficacy of Biometrics for Positive Identification.

Science.gov (United States)

Sauerwein, Kelly; Saul, Tiffany B; Steadman, Dawnie Wolfe; Boehnen, Chris B

2017-11-01

Biometrics, unique measurable physiological and behavioral characteristics, are used to identify individuals in a variety of scenarios, including forensic investigations. However, data on the longevity of these indicators are incomplete. This study demonstrated that iris and fingerprint biometric data can be obtained up to four days postmortem in warmer seasons and 50 + days in the winter. It has been generally believed, but never studied, that iris recognition is only obtainable within the first 24 hours after death. However, this study showed that they remain viable for longer (2-34 days) depending upon the environmental conditions. Temperature, precipitation, insects, and scavenger activity were the primary factors affecting the retention of biometrics in decomposing human remains. While this study is an initial step in determining the utility of physiological biometrics across postmortem time, biometric research has the potential to make important contributions to human identification and the law enforcement, military, and medicolegal communities. © 2017 American Academy of Forensic Sciences.
Biometrics — Developments and Potential

NARCIS (Netherlands)

Meuwly, Didier; Veldhuis, Raymond N.J.

2014-01-01

This article describes the use of biometric technology in forensic science, for the development of new methods and tools, improving the current forensic biometric applications, and allowing for the creation of new ones. The article begins with a definition and a summary of the development of this
Biometric Communication Research for Television.

Science.gov (United States)

Malik, M. F.

Biometric communication research is defined as research dealing with the information impact of a film or television show, photographic picture, painting, exhibition, display, or any literary or functional texts or verbal stimuli on human beings, both as individuals and in groups (mass audiences). Biometric communication research consists of a…
Entropy Measurement for Biometric Verification Systems.

Science.gov (United States)

Lim, Meng-Hui; Yuen, Pong C

2016-05-01

Biometric verification systems are designed to accept multiple similar biometric measurements per user due to inherent intrauser variations in the biometric data. This is important to preserve reasonable acceptance rate of genuine queries and the overall feasibility of the recognition system. However, such acceptance of multiple similar measurements decreases the imposter's difficulty of obtaining a system-acceptable measurement, thus resulting in a degraded security level. This deteriorated security needs to be measurable to provide truthful security assurance to the users. Entropy is a standard measure of security. However, the entropy formula is applicable only when there is a single acceptable possibility. In this paper, we develop an entropy-measuring model for biometric systems that accepts multiple similar measurements per user. Based on the idea of guessing entropy, the proposed model quantifies biometric system security in terms of adversarial guessing effort for two practical attacks. Excellent agreement between analytic and experimental simulation-based measurement results on a synthetic and a benchmark face dataset justify the correctness of our model and thus the feasibility of the proposed entropy-measuring approach.
A concatenated coding scheme for biometric template protection

NARCIS (Netherlands)

Shao, X.; Xu, H.; Veldhuis, Raymond N.J.; Slump, Cornelis H.

2012-01-01

Cryptography may mitigate the privacy problem in biometric recognition systems. However, cryptography technologies lack error-tolerance and biometric samples cannot be reproduced exactly, rising the robustness problem. The biometric template protection system needs a good feature extraction
International Work-Conference on Time Series

CERN Document Server

Pomares, Héctor; Valenzuela, Olga

2017-01-01

This volume of selected and peer-reviewed contributions on the latest developments in time series analysis and forecasting updates the reader on topics such as analysis of irregularly sampled time series, multi-scale analysis of univariate and multivariate time series, linear and non-linear time series models, advanced time series forecasting methods, applications in time series analysis and forecasting, advanced methods and online learning in time series and high-dimensional and complex/big data time series. The contributions were originally presented at the International Work-Conference on Time Series, ITISE 2016, held in Granada, Spain, June 27-29, 2016. The series of ITISE conferences provides a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary rese arch encompassing the disciplines of comput...
Biometric Passport Validation Scheme using Radio Frequency Identification

OpenAIRE

V.K. Narendira Kumar; B. Srinivasan

2013-01-01

Biometric passports issued nowadays have an embedded RFID chip that carries digitally signed biometric information. This RIFD chip is integrated into the cover of a passport, called a biometric passport. Electronic passports as it is sometimes called, represents a bold initiative in the deployment of two new technologies: RIFD and biometrics such as face, fingerprints, palm prints and iris. The electronic passport is the privacy and security risks that arise by embedding RFID technology. The ...
Voice Biometrics for Information Assurance Applications

National Research Council Canada - National Science Library

Kang, George

2002-01-01

.... The ultimate goal of voice biometrics is to enable the use of voice as a password. Voice biometrics are "man-in-the-loop" systems in which system performance is significantly dependent on human performance...
Biometrics for electronic health records.

Science.gov (United States)

Flores Zuniga, Alejandro Enrique; Win, Khin Than; Susilo, Willy

2010-10-01

Securing electronic health records, in scenarios in which the provision of care services is share among multiple actors, could become a complex and costly activity. Correct identification of patients and physician, protection of privacy and confidentiality, assignment of access permissions for healthcare providers and resolutions of conflicts rise as main points of concern in the development of interconnected health information networks. Biometric technologies have been proposed as a possible technological solution for these issues due to its ability to provide a mechanism for unique verification of an individual identity. This paper presents an analysis of the benefit as well as disadvantages offered by biometric technology. A comparison between this technology and more traditional identification methods is used to determine the key benefits and flaws of the use biometric in health information systems. The comparison as been made considering the viability of the technologies for medical environments, global security needs, the contemplation of a share care environment and the costs involved in the implementation and maintenance of such technologies. This paper also discusses alternative uses for biometrics technologies in health care environments. The outcome of this analysis lays in the fact that even when biometric technologies offer several advantages over traditional method of identification, they are still in the early stages of providing a suitable solution for a health care environment.
From Networks to Time Series

Science.gov (United States)

Shimada, Yutaka; Ikeguchi, Tohru; Shigehara, Takaomi

2012-10-01

In this Letter, we propose a framework to transform a complex network to a time series. The transformation from complex networks to time series is realized by the classical multidimensional scaling. Applying the transformation method to a model proposed by Watts and Strogatz [Nature (London) 393, 440 (1998)], we show that ring lattices are transformed to periodic time series, small-world networks to noisy periodic time series, and random networks to random time series. We also show that these relationships are analytically held by using the circulant-matrix theory and the perturbation theory of linear operators. The results are generalized to several high-dimensional lattices.
Secure method for biometric-based recognition with integrated cryptographic functions.

Science.gov (United States)

Chiou, Shin-Yan

2013-01-01

Biometric systems refer to biometric technologies which can be used to achieve authentication. Unlike cryptography-based technologies, the ratio for certification in biometric systems needs not to achieve 100% accuracy. However, biometric data can only be directly compared through proximal access to the scanning device and cannot be combined with cryptographic techniques. Moreover, repeated use, improper storage, or transmission leaks may compromise security. Prior studies have attempted to combine cryptography and biometrics, but these methods require the synchronization of internal systems and are vulnerable to power analysis attacks, fault-based cryptanalysis, and replay attacks. This paper presents a new secure cryptographic authentication method using biometric features. The proposed system combines the advantages of biometric identification and cryptographic techniques. By adding a subsystem to existing biometric recognition systems, we can simultaneously achieve the security of cryptographic technology and the error tolerance of biometric recognition. This method can be used for biometric data encryption, signatures, and other types of cryptographic computation. The method offers a high degree of security with protection against power analysis attacks, fault-based cryptanalysis, and replay attacks. Moreover, it can be used to improve the confidentiality of biological data storage and biodata identification processes. Remote biometric authentication can also be safely applied.
Secure Method for Biometric-Based Recognition with Integrated Cryptographic Functions

Directory of Open Access Journals (Sweden)

Shin-Yan Chiou

2013-01-01

Full Text Available Biometric systems refer to biometric technologies which can be used to achieve authentication. Unlike cryptography-based technologies, the ratio for certification in biometric systems needs not to achieve 100% accuracy. However, biometric data can only be directly compared through proximal access to the scanning device and cannot be combined with cryptographic techniques. Moreover, repeated use, improper storage, or transmission leaks may compromise security. Prior studies have attempted to combine cryptography and biometrics, but these methods require the synchronization of internal systems and are vulnerable to power analysis attacks, fault-based cryptanalysis, and replay attacks. This paper presents a new secure cryptographic authentication method using biometric features. The proposed system combines the advantages of biometric identification and cryptographic techniques. By adding a subsystem to existing biometric recognition systems, we can simultaneously achieve the security of cryptographic technology and the error tolerance of biometric recognition. This method can be used for biometric data encryption, signatures, and other types of cryptographic computation. The method offers a high degree of security with protection against power analysis attacks, fault-based cryptanalysis, and replay attacks. Moreover, it can be used to improve the confidentiality of biological data storage and biodata identification processes. Remote biometric authentication can also be safely applied.
Recognition Errors Control in Biometric Identification Cryptosystems

Directory of Open Access Journals (Sweden)

Vladimir Ivanovich Vasilyev

2015-06-01

Full Text Available The method of biometric cryptosystem designed on the basis of fuzzy extractor, in which main disadvantages of biometric and cryptographic systems are absent, is considered. The main idea of this work is a control of identity recognition errors with use of fuzzy extractor which operates with Reed – Solomon correcting code. The fingerprint features vector is considered as a biometric user identifier.
Towards a General Definition of Biometric Systems

OpenAIRE

Mirko Cubrilo; Miroslav Baca; Markus Schatten

2009-01-01

A foundation for closing the gap between biometrics in the narrower and the broader perspective is presented trough a conceptualization of biometric systems in both perspectives. A clear distinction between verification, identification and classification systems is made as well as shown that there are additional classes of biometric systems. In the end a Unified Modeling Language model is developed showing the connections between the two perspectives.
A Systems Approach to Biometrics in the Military Domain.

Science.gov (United States)

Wilson, Lauren; Gahan, Michelle; Lennard, Chris; Robertson, James

2018-02-21

Forensic biometrics is the application of forensic science principles to physical and behavioral characteristics. Forensic biometrics is a secondary sub-system in the forensic science "system of systems," which describes forensic science as a sub-system in the larger criminal justice, law enforcement, intelligence, and military system. The purpose of this paper is to discuss biometrics in the military domain and integration into the wider forensic science system of systems. The holistic system thinking methodology was applied to the U.S. biometric system to map it to the system of systems framework. The U.S. biometric system is used as a case study to help guide other countries to develop military biometric systems that are integrated and interoperable at the whole-of-government level. The aim is to provide the system of systems framework for agencies to consider for proactive design of biometric systems. © 2018 American Academy of Forensic Sciences.
Logistic Map for Cancellable Biometrics

Science.gov (United States)

Supriya, V. G., Dr; Manjunatha, Ramachandra, Dr

2017-08-01

This paper presents design and implementation of secured biometric template protection system by transforming the biometric template using binary chaotic signals and 3 different key streams to obtain another form of template and demonstrating its efficiency by the results and investigating on its security through analysis including, key space analysis, information entropy and key sensitivity analysis.
Anatomy of biometric passports.

Science.gov (United States)

Malčík, Dominik; Drahanský, Martin

2012-01-01

Travelling is becoming available for more and more people. Millions of people are on a way every day. That is why a better control over global human transfer and a more reliable identity check is desired. A recent trend in a field of personal identification documents is to use RFID (Radio Frequency Identification) technology and biometrics, especially (but not only) in passports. This paper provides an insight into the electronic passports (also called e-passport or ePassport) implementation chosen in the Czech Republic. Such a summary is needed for further studies of biometric passports implementation security and biometric passports analysis. A separate description of the Czech solution is a prerequisite for a planned analysis, because of the uniqueness of each implementation. (Each country can choose the implementation details within a range specified by the ICAO (International Civil Aviation Organisation); moreover, specific security mechanisms are optional and can be omitted).
Biometrics can help protect and safeguard.

Science.gov (United States)

Oakes, Shaun

2017-06-01

Shaun Oakes, managing director at ievo, a north-east England-based manufacturer of biometric fingerprint readers, argues that growing use of biometrics technology can improve security and afford better protection to premises, valuable items, and people, across an ever-busier NHS.
Handwriting: Feature Correlation Analysis for Biometric Hashes

Science.gov (United States)

Vielhauer, Claus; Steinmetz, Ralf

2004-12-01

In the application domain of electronic commerce, biometric authentication can provide one possible solution for the key management problem. Besides server-based approaches, methods of deriving digital keys directly from biometric measures appear to be advantageous. In this paper, we analyze one of our recently published specific algorithms of this category based on behavioral biometrics of handwriting, the biometric hash. Our interest is to investigate to which degree each of the underlying feature parameters contributes to the overall intrapersonal stability and interpersonal value space. We will briefly discuss related work in feature evaluation and introduce a new methodology based on three components: the intrapersonal scatter (deviation), the interpersonal entropy, and the correlation between both measures. Evaluation of the technique is presented based on two data sets of different size. The method presented will allow determination of effects of parameterization of the biometric system, estimation of value space boundaries, and comparison with other feature selection approaches.

Handwriting: Feature Correlation Analysis for Biometric Hashes

Directory of Open Access Journals (Sweden)

Ralf Steinmetz

2004-04-01

Full Text Available In the application domain of electronic commerce, biometric authentication can provide one possible solution for the key management problem. Besides server-based approaches, methods of deriving digital keys directly from biometric measures appear to be advantageous. In this paper, we analyze one of our recently published specific algorithms of this category based on behavioral biometrics of handwriting, the biometric hash. Our interest is to investigate to which degree each of the underlying feature parameters contributes to the overall intrapersonal stability and interpersonal value space. We will briefly discuss related work in feature evaluation and introduce a new methodology based on three components: the intrapersonal scatter (deviation, the interpersonal entropy, and the correlation between both measures. Evaluation of the technique is presented based on two data sets of different size. The method presented will allow determination of effects of parameterization of the biometric system, estimation of value space boundaries, and comparison with other feature selection approaches.
Biometric technology authentication, biocryptography, and cloud-based architecture

CERN Document Server

Das, Ravi

2014-01-01

Most biometric books are either extraordinarily technical for technophiles or extremely elementary for the lay person. Striking a balance between the two, Biometric Technology: Authentication, Biocryptography, and Cloud-Based Architecture is ideal for business, IT, or security managers that are faced with the task of making purchasing, migration, or adoption decisions. It brings biometrics down to an understandable level, so that you can immediately begin to implement the concepts discussed.Exploring the technological and social implications of widespread biometric use, the book considers the
Duality between Time Series and Networks

Science.gov (United States)

Campanharo, Andriana S. L. O.; Sirer, M. Irmak; Malmgren, R. Dean; Ramos, Fernando M.; Amaral, Luís A. Nunes.

2011-01-01

Studying the interaction between a system's components and the temporal evolution of the system are two common ways to uncover and characterize its internal workings. Recently, several maps from a time series to a network have been proposed with the intent of using network metrics to characterize time series. Although these maps demonstrate that different time series result in networks with distinct topological properties, it remains unclear how these topological properties relate to the original time series. Here, we propose a map from a time series to a network with an approximate inverse operation, making it possible to use network statistics to characterize time series and time series statistics to characterize networks. As a proof of concept, we generate an ensemble of time series ranging from periodic to random and confirm that application of the proposed map retains much of the information encoded in the original time series (or networks) after application of the map (or its inverse). Our results suggest that network analysis can be used to distinguish different dynamic regimes in time series and, perhaps more importantly, time series analysis can provide a powerful set of tools that augment the traditional network analysis toolkit to quantify networks in new and useful ways. PMID:21858093
Content-based Image Hiding Method for Secure Network Biometric Verification

Directory of Open Access Journals (Sweden)

Xiangjiu Che

2011-08-01

Full Text Available For secure biometric verification, most existing methods embed biometric information directly into the cover image, but content correlation analysis between the biometric image and the cover image is often ignored. In this paper, we propose a novel biometric image hiding approach based on the content correlation analysis to protect the network-based transmitted image. By using principal component analysis (PCA, the content correlation between the biometric image and the cover image is firstly analyzed. Then based on particle swarm optimization (PSO algorithm, some regions of the cover image are selected to represent the biometric image, in which the cover image can carry partial content of the biometric image. As a result of the correlation analysis, the unrepresented part of the biometric image is embedded into the cover image by using the discrete wavelet transform (DWT. Combined with human visual system (HVS model, this approach makes the hiding result perceptually invisible. The extensive experimental results demonstrate that the proposed hiding approach is robust against some common frequency and geometric attacks; it also provides an effective protection for the secure biometric verification.
Long time series

DEFF Research Database (Denmark)

Hisdal, H.; Holmqvist, E.; Hyvärinen, V.

Awareness that emission of greenhouse gases will raise the global temperature and change the climate has led to studies trying to identify such changes in long-term climate and hydrologic time series. This report, written by the......Awareness that emission of greenhouse gases will raise the global temperature and change the climate has led to studies trying to identify such changes in long-term climate and hydrologic time series. This report, written by the...
Fusion of Multimodal Biometrics using Feature and Score Level Fusion

OpenAIRE

Mohana Prakash, S.; Betty, P.; Sivanarulselvan, K.

2016-01-01

Biometrics is used to uniquely identify a person‘s individual based on physical and behavioural characteristics. Unimodal biometric system contains various problems such as degree of freedom, spoof attacks, non-universality, noisy data and error rates. Multimodal biometrics is introduced to overcome the limitations in Unimodal biometrics. The presented methodology extracts the features of four biometric traits such as fingerprint, palm, iris and retina. Then extracted features are fused in th...
Behavioural Biometrics for Application in Biomedicine

Czech Academy of Sciences Publication Activity Database

Schlenker, Anna; Šárek, M.

2013-01-01

Roč. 1, č. 1 (2013), s. 56-56 ISSN 1805-8698. [EFMI 2013 Special Topic Conference. 17.04.2013-19.04.2013, Prague] Institutional support: RVO:67985807 Keywords : biometrics * behavioural biometrics * keystroke dynamics * mouse dynamics Subject RIV: IN - Informatics, Computer Science
Fourier domain asymmetric cryptosystem for privacy protected multimodal biometric security

Science.gov (United States)

Choudhury, Debesh

2016-04-01

We propose a Fourier domain asymmetric cryptosystem for multimodal biometric security. One modality of biometrics (such as face) is used as the plaintext, which is encrypted by another modality of biometrics (such as fingerprint). A private key is synthesized from the encrypted biometric signature by complex spatial Fourier processing. The encrypted biometric signature is further encrypted by other biometric modalities, and the corresponding private keys are synthesized. The resulting biometric signature is privacy protected since the encryption keys are provided by the human, and hence those are private keys. Moreover, the decryption keys are synthesized using those private encryption keys. The encrypted signatures are decrypted using the synthesized private keys and inverse complex spatial Fourier processing. Computer simulations demonstrate the feasibility of the technique proposed.
On the Quantification of Aging Effects on Biometric Features

OpenAIRE

Lanitis , Andreas; Tsapatsoulis , Nicolas

2010-01-01

International audience; Biometric templates are often used in intelligent human computer interaction systems that include automated access control and personalization of user interaction. The effectiveness of biometric systems is directly linked with aging that causes modifications on biometric features. For example the long term performance of person identification systems decreases as biometric templates derived from aged subjects may display substantial differences when compared to referen...
BIOMETRIC IDENTITY VERIFICATION IN HEALTH SERVICES: A BIOMETRIC SURVEILLANCE PRACTICE IN TURKEY

Directory of Open Access Journals (Sweden)

İlker ŞİRİN

2014-08-01

Full Text Available Determination or verification of identity with biometric methods has a widespread use especially at borders for security reasons. Social Security Institution transferred the biometric identity verification practice to health sercives that are provided by private and university hospitals. The risks of the new system considering the privacy of personal data are under debate. Although there are announcements or manuals of Social Security Institution regarding the implementation and legislation for data sharing and security exists, lack of a national data protection law brings with it security gaps.
A Course in Time Series Analysis

CERN Document Server

Peña, Daniel; Tsay, Ruey S

2011-01-01

New statistical methods and future directions of research in time series A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, a
Biometric features and privacy : condemned, based upon your finger print

NARCIS (Netherlands)

Bullee, Jan-Willem; Veldhuis, Raymond N.J.

What information is available in biometric features besides that needed for the biometric recognition process? What if a biometric feature contains Personally Identifiable Information? Will the whole biometric system become a threat to privacy? This paper is an attempt to quantifiy the link between
Evaluation of Biometric Systems

OpenAIRE

El-Abed , Mohamad; Charrier , Christophe

2012-01-01

International audience; Biometrics is considered as a promising solution among traditional methods based on "what we own" (such as a key) or "what we know" (such as a password). It is based on "what we are" and "how we behave". Few people know that biometrics have been used for ages for identification or signature purposes. In 1928 for example, fingerprints were used for women clerical employees of Los Angeles police department as depicted in Figure 1. Fingerprints were also already used as a...
Multispectral biometrics systems and applications

CERN Document Server

Zhang, David; Gong, Yazhuo

2016-01-01

Describing several new biometric technologies, such as high-resolution fingerprint, finger-knuckle-print, multi-spectral backhand, 3D fingerprint, tongueprint, 3D ear, and multi-spectral iris recognition technologies, this book analyzes a number of efficient feature extraction, matching and fusion algorithms and how potential systems have been developed. Focusing on how to develop new biometric technologies based on the requirements of applications, and how to design efficient algorithms to deliver better performance, the work is based on the author’s research with experimental results under different challenging conditions described in the text. The book offers a valuable resource for researchers, professionals and postgraduate students working in the fields of computer vision, pattern recognition, biometrics, and security applications, amongst others.
A STUDY ON BIOMETRIC TEMPLATE SECURITY

Directory of Open Access Journals (Sweden)

N. Radha

2010-07-01

Full Text Available The increasing popularity of biometrics and cryptography is driven by the widespread stipulation on information security. Abundant efforts have been made in developing successful methods in these areas in order to accomplish an enhanced level of information security. There are two dominant issues in information security enhancement. One is to defend the user ownership and control the access to information by authenticating an individual’s identity. The other is to make sure the privacy and integrity of information and to secure communication. Cryptography is the science of writing in secret code. Secret-key cryptography and public-key cryptography are the two most important cryptographic architectures. The security of a cryptographic system is reliant on the secrecy of the cryptographic key. Biometric authentication or simply biometrics refers to establishing automatic personal recognition based on the physical and behavioral characteristics of an individual (e.g. face, voice, fingerprint, gait, hand geometry, iris, gene, etc.. Biometrics offers superior security and easier than traditional identity authentication systems (based on passwords and cryptographic keys.Since biometrics characteristics are naturally related with a particular individual, making them insusceptible to being stolen, forgotten, lost or attached. This paper presents a survey on various techniques proposed earlier in developing an authentication system for ensuring individual’s information security by combining biometric characteristics of that particular individual and the cryptographic techniques. In addition, it provides some fundamental idea for future research that may help in eliminating the problems associated with the present authentication systems.
Biometric security and privacy opportunities & challenges in the big data era

CERN Document Server

Al-maadeed, Somaya; Bouridane, Ahmed; Crookes, Prof; Beghdadi, Azeddine

2017-01-01

This book highlights recent research advances on biometrics using new methods such as deep learning, nonlinear graph embedding, fuzzy approaches, and ensemble learning. Included are special biometric technologies related to privacy and security issues, such as quality issue, biometric template protection, and anti-spoofing. The book also focuses on several emerging topics such as big data issues, mobile biometrics and multispectral biometrics, and includes a number of new biometrics such as vein pattern, acoustic biometrics, eye-blinking EOG, ECG, gait and handwriting. Authors also show how to use biometrics in cyber security applications and its relevant legal matters under EU legislation. The contributors cover the topics, their methods, and their applications in depth.
Transfer Function Control for Biometric Monitoring System

Science.gov (United States)

Chmiel, Alan J. (Inventor); Humphreys, Bradley T. (Inventor); Grodinsky, Carlos M. (Inventor)

2015-01-01

A modular apparatus for acquiring biometric data may include circuitry operative to receive an input signal indicative of a biometric condition, the circuitry being configured to process the input signal according to a transfer function thereof and to provide a corresponding processed input signal. A controller is configured to provide at least one control signal to the circuitry to programmatically modify the transfer function of the modular system to facilitate acquisition of the biometric data.
Biometric Authentication System using Non-Linear Chaos

OpenAIRE

Dr.N.Krishnan; A.Senthil Arumugam,

2010-01-01

A major concern nowadays for any Biometric Credential Management System is its potential vulnerability to protect its information sources; i.e. protecting a genuine user’s template from both internal and external threats. These days’ biometric authentication systems face various risks. One of the most serious threats is the ulnerability of the template's database. An attacker with access to a reference template could try to impersonate a legitimate user by reconstructing the biometric sample...
Novel continuous authentication using biometrics

Science.gov (United States)

Dubey, Prakash; Patidar, Rinku; Mishra, Vikas; Norman, Jasmine; Mangayarkarasi, R.

2017-11-01

We explore whether a classifier can consistent1y verify c1ients and interact with the computer using camera and behavior of users. In this paper we propose a new way of authentication of user which wi1l capture many images of user in random time and ana1ysis of its touch biometric behavior. In this system experiment the touch conduct of a c1ient/user between an en1istment stage is stored in the database and it is checked its mean time behavior during equa1 partition of time. This touch behavior wi1l ab1e to accept or reject the user. This wi1l modify the use of biometric more accurate to use. In this system the work p1an going to perform is the user wi1l ask single time to a1low to take it picture before 1ogin. Then it wi1l take images of user without permission of user automatica1ly and store in the database. This images and existing image of user wi1l be compare and reject or accept wi1l depend on its comparison. The user touch behavior wi1l keep storing with number of touch make in equa1 amount of time of the user. This touch behavior and image wi1l fina1ly perform authentication of the user automatically.
Anatomy of Biometric Passports

Directory of Open Access Journals (Sweden)

Dominik Malčík

2012-01-01

Full Text Available Travelling is becoming available for more and more people. Millions of people are on a way every day. That is why a better control over global human transfer and a more reliable identity check is desired. A recent trend in a field of personal identification documents is to use RFID (Radio Frequency Identification technology and biometrics, especially (but not only in passports. This paper provides an insight into the electronic passports (also called e-passport or ePassport implementation chosen in the Czech Republic. Such a summary is needed for further studies of biometric passports implementation security and biometric passports analysis. A separate description of the Czech solution is a prerequisite for a planned analysis, because of the uniqueness of each implementation. (Each country can choose the implementation details within a range specified by the ICAO (International Civil Aviation Organisation; moreover, specific security mechanisms are optional and can be omitted.

Anatomy of Biometric Passports

Science.gov (United States)

Malčík, Dominik; Drahanský, Martin

2012-01-01

Travelling is becoming available for more and more people. Millions of people are on a way every day. That is why a better control over global human transfer and a more reliable identity check is desired. A recent trend in a field of personal identification documents is to use RFID (Radio Frequency Identification) technology and biometrics, especially (but not only) in passports. This paper provides an insight into the electronic passports (also called e-passport or ePassport) implementation chosen in the Czech Republic. Such a summary is needed for further studies of biometric passports implementation security and biometric passports analysis. A separate description of the Czech solution is a prerequisite for a planned analysis, because of the uniqueness of each implementation. (Each country can choose the implementation details within a range specified by the ICAO (International Civil Aviation Organisation); moreover, specific security mechanisms are optional and can be omitted). PMID:22969272
Biometric verificaton and biometric identification of a person by methods of statistical analysis of digitized iris images

Czech Academy of Sciences Publication Activity Database

Machala, L.; Pospíšil, Jaroslav

40-41, - (2001), s. 155-162 ISSN 0231-9365 Institutional research plan: CEZ:AV0Z1010921 Keywords : biometric verification * biometric idntification * human eye`s iris * statistical error of type I * statistical erroer II * charasteristic iris vector Subject RIV: BH - Optics, Masers, Lasers
A framework for biometric playtesting of games

OpenAIRE

Janssen, Dirk; Calvi, Licia; Gualeni, Stefano; Foundation of Digital Games Conference

2013-01-01

The described framework is meant to assist game developers in using biometric (psychophysiological) methods while playtesting. Biometric methods can give developers a valuable additional window on the playtester's experience.
Voice Biometrics over the Internet in the Framework of COST Action 275

Directory of Open Access Journals (Sweden)

Evans Nicholas WD

2004-01-01

Full Text Available The emerging field of biometric authentication over the Internet requires both robust person authentication and secure computer network protocols. This paper presents investigations of vocal biometric person authentication over the Internet, both at the protocol and authentication robustness levels. As part of this study, an appropriate client-server architecture for biometrics on the Internet is proposed and implemented. It is shown that the transmission of raw biometric data in this application is likely to result in unacceptably long delays in the process. On the other hand, by using data models (or features, the transmission time can be reduced to an acceptable level. The use of encryption/decryption for enhancing the data security in the proposed client-server link and its effects on the transmission time are also examined. Furthermore, the scope of the investigations includes an analysis of the effects of packet loss and speech coding on speaker verification performance. It is experimentally demonstrated that whilst the adverse effects of packet loss can be negligible, the encoding of speech, particularly at a low bit rate, can reduce the verification accuracy considerably. The paper details the experimental investigations conducted and presents an analysis of the results.
Kolmogorov Space in Time Series Data

OpenAIRE

Kanjamapornkul, K.; Pinčák, R.

2016-01-01

We provide the proof that the space of time series data is a Kolmogorov space with $T_{0}$-separation axiom using the loop space of time series data. In our approach we define a cyclic coordinate of intrinsic time scale of time series data after empirical mode decomposition. A spinor field of time series data comes from the rotation of data around price and time axis by defining a new extradimension to time series data. We show that there exist hidden eight dimensions in Kolmogorov space for ...
Hand Grasping Synergies As Biometrics.

Science.gov (United States)

Patel, Vrajeshri; Thukral, Poojita; Burns, Martin K; Florescu, Ionut; Chandramouli, Rajarathnam; Vinjamuri, Ramana

2017-01-01

Recently, the need for more secure identity verification systems has driven researchers to explore other sources of biometrics. This includes iris patterns, palm print, hand geometry, facial recognition, and movement patterns (hand motion, gait, and eye movements). Identity verification systems may benefit from the complexity of human movement that integrates multiple levels of control (neural, muscular, and kinematic). Using principal component analysis, we extracted spatiotemporal hand synergies (movement synergies) from an object grasping dataset to explore their use as a potential biometric. These movement synergies are in the form of joint angular velocity profiles of 10 joints. We explored the effect of joint type, digit, number of objects, and grasp type. In its best configuration, movement synergies achieved an equal error rate of 8.19%. While movement synergies can be integrated into an identity verification system with motion capture ability, we also explored a camera-ready version of hand synergies-postural synergies. In this proof of concept system, postural synergies performed well, but only when specific postures were chosen. Based on these results, hand synergies show promise as a potential biometric that can be combined with other hand-based biometrics for improved security.
Hand Grasping Synergies As Biometrics

Directory of Open Access Journals (Sweden)

Ramana Vinjamuri

2017-05-01

Full Text Available Recently, the need for more secure identity verification systems has driven researchers to explore other sources of biometrics. This includes iris patterns, palm print, hand geometry, facial recognition, and movement patterns (hand motion, gait, and eye movements. Identity verification systems may benefit from the complexity of human movement that integrates multiple levels of control (neural, muscular, and kinematic. Using principal component analysis, we extracted spatiotemporal hand synergies (movement synergies from an object grasping dataset to explore their use as a potential biometric. These movement synergies are in the form of joint angular velocity profiles of 10 joints. We explored the effect of joint type, digit, number of objects, and grasp type. In its best configuration, movement synergies achieved an equal error rate of 8.19%. While movement synergies can be integrated into an identity verification system with motion capture ability, we also explored a camera-ready version of hand synergies—postural synergies. In this proof of concept system, postural synergies performed well, but only when specific postures were chosen. Based on these results, hand synergies show promise as a potential biometric that can be combined with other hand-based biometrics for improved security.
Biometric National Identification Number Generation for Secure ...

African Journals Online (AJOL)

Biometric National Identification Number Generation for Secure Network Authentication Based Fingerprint. ... Username, Password, Remember me, or Register ... In this paper an authentication based finger print biometric system is proposed ...
On the Use of Running Trends as Summary Statistics for Univariate Time Series and Time Series Association

OpenAIRE

Trottini, Mario; Vigo, Isabel; Belda, Santiago

2015-01-01

Given a time series, running trends analysis (RTA) involves evaluating least squares trends over overlapping time windows of L consecutive time points, with overlap by all but one observation. This produces a new series called the “running trends series,” which is used as summary statistics of the original series for further analysis. In recent years, RTA has been widely used in climate applied research as summary statistics for time series and time series association. There is no doubt that ...
Case studies of the use of biometrics technologies to reduce fraud in governmental and industrial environments

Science.gov (United States)

Bordes, Roy N.

1998-12-01

The purpose of this presentation is to enlighten the reader on the advancements that have been made in the field of biometrics technology as it relates to government and industrial-type applications. The term 'biometrics' is defined as, 'Any technology that uses electronically scanned graphical information for identification purposes.' Biometric technology was for a long time in the experimental stages, with many BETA test projects that were really not applicable to industrial markets. During the course of this presentation, we will show that biometrics applications do work, can develop positive returns on investment, but from a security standpoint have some major application problems that still need to be overcome. We will also address which biometric technologies have a better future in the security world than others.
SURVEY OF BIOMETRIC SYSTEMS USING IRIS RECOGNITION

OpenAIRE

S.PON SANGEETHA; DR.M.KARNAN

2014-01-01

The security plays an important role in any type of organization in today’s life. Iris recognition is one of the leading automatic biometric systems in the area of security which is used to identify the individual person. Biometric systems include fingerprints, facial features, voice recognition, hand geometry, handwriting, the eye retina and the most secured one presented in this paper, the iris recognition. Biometric systems has become very famous in security systems because it is not possi...
THRIVE: threshold homomorphic encryption based secure and privacy preserving biometric verification system

Science.gov (United States)

Karabat, Cagatay; Kiraz, Mehmet Sabir; Erdogan, Hakan; Savas, Erkay

2015-12-01

In this paper, we introduce a new biometric verification and template protection system which we call THRIVE. The system includes novel enrollment and authentication protocols based on threshold homomorphic encryption where a private key is shared between a user and a verifier. In the THRIVE system, only encrypted binary biometric templates are stored in a database and verification is performed via homomorphically randomized templates, thus, original templates are never revealed during authentication. Due to the underlying threshold homomorphic encryption scheme, a malicious database owner cannot perform full decryption on encrypted templates of the users in the database. In addition, security of the THRIVE system is enhanced using a two-factor authentication scheme involving user's private key and biometric data. Using simulation-based techniques, the proposed system is proven secure in the malicious model. The proposed system is suitable for applications where the user does not want to reveal her biometrics to the verifier in plain form, but needs to prove her identity by using biometrics. The system can be used with any biometric modality where a feature extraction method yields a fixed size binary template and a query template is verified when its Hamming distance to the database template is less than a threshold. The overall connection time for the proposed THRIVE system is estimated to be 336 ms on average for 256-bit biometric templates on a desktop PC running with quad core 3.2 GHz CPUs at 10 Mbit/s up/down link connection speed. Consequently, the proposed system can be efficiently used in real-life applications.
On enabling secure applications through off-line biometric identification

Energy Technology Data Exchange (ETDEWEB)

Davida, G.I. [Univ. of Wisconsin, Milwaukee, WI (United States); Frankel, Y. [CertCo LLC, New York, NY (United States); Matt, B.J. [Sandia National Labs., Albuquerque, NM (United States)

1998-04-01

In developing secure applications and systems, the designers often must incorporate secure user identification in the design specification. In this paper, the authors study secure off line authenticated user identification schemes based on a biometric system that can measure a user`s biometric accurately (up to some Hamming distance). The schemes presented here enhance identification and authorization in secure applications by binding a biometric template with authorization information on a token such as a magnetic strip. Also developed here are schemes specifically designed to minimize the compromise of a user`s private biometrics data, encapsulated in the authorization information, without requiring secure hardware tokens. In this paper the authors furthermore study the feasibility of biometrics performing as an enabling technology for secure system and application design. The authors investigate a new technology which allows a user`s biometrics to facilitate cryptographic mechanisms.
On enabling secure applications through off-line biometric identification

International Nuclear Information System (INIS)

Davida, G.I.; Frankel, Y.; Matt, B.J.

1998-04-01

In developing secure applications and systems, the designers often must incorporate secure user identification in the design specification. In this paper, the authors study secure off line authenticated user identification schemes based on a biometric system that can measure a user's biometric accurately (up to some Hamming distance). The schemes presented here enhance identification and authorization in secure applications by binding a biometric template with authorization information on a token such as a magnetic strip. Also developed here are schemes specifically designed to minimize the compromise of a user's private biometrics data, encapsulated in the authorization information, without requiring secure hardware tokens. In this paper the authors furthermore study the feasibility of biometrics performing as an enabling technology for secure system and application design. The authors investigate a new technology which allows a user's biometrics to facilitate cryptographic mechanisms
Biometric recognition via fixation density maps

Science.gov (United States)

Rigas, Ioannis; Komogortsev, Oleg V.

2014-05-01

This work introduces and evaluates a novel eye movement-driven biometric approach that employs eye fixation density maps for person identification. The proposed feature offers a dynamic representation of the biometric identity, storing rich information regarding the behavioral and physical eye movement characteristics of the individuals. The innate ability of fixation density maps to capture the spatial layout of the eye movements in conjunction with their probabilistic nature makes them a particularly suitable option as an eye movement biometrical trait in cases when free-viewing stimuli is presented. In order to demonstrate the effectiveness of the proposed approach, the method is evaluated on three different datasets containing a wide gamut of stimuli types, such as static images, video and text segments. The obtained results indicate a minimum EER (Equal Error Rate) of 18.3 %, revealing the perspectives on the utilization of fixation density maps as an enhancing biometrical cue during identification scenarios in dynamic visual environments.
Extracting forensic evidence from biometric devices

Science.gov (United States)

Geradts, Zeno J.; Ruifrok, Arnout C.

2003-08-01

Over the past few years, both large multinationals and governments have begun to contribute to even larger projects on biometric devices. Terrorist attacks in America and in other countries have highlighted the need for better identification systems for people as well as improved systems for controlling access to buildings. Another reason for investment in Research and Development in Biometric Devices, is the massive growth in internet-based systems -- whether for e-commerce, e-government or internal processes within organizations. The interface between the system and the user is routinely abused, as people have to remember many complex passwords and handle tokens of various types. In this paper an overview is given of the information that is important to know before an examination of such is systems can be done in a forensic proper way. In forensic evidence with biometric devices the forensic examiner should consider the possibilities of tampering with the biometric systems or the possibilities of unauthorized access before drawing conclusions.
Multiple Indicator Stationary Time Series Models.

Science.gov (United States)

Sivo, Stephen A.

2001-01-01

Discusses the propriety and practical advantages of specifying multivariate time series models in the context of structural equation modeling for time series and longitudinal panel data. For time series data, the multiple indicator model specification improves on classical time series analysis. For panel data, the multiple indicator model…
Promises and Challenges in Continuous Tracking Utilizing Amino Acids in Skin Secretions for Active Multi-Factor Biometric Authentication for Cybersecurity.

Science.gov (United States)

Agudelo, Juliana; Privman, Vladimir; Halámek, Jan

2017-07-05

We consider a new concept of biometric-based cybersecurity systems for active authentication by continuous tracking, which utilizes biochemical processing of metabolites present in skin secretions. Skin secretions contain a large number of metabolites and small molecules that can be targeted for analysis. Here we argue that amino acids found in sweat can be exploited for the establishment of an amino acid profile capable of identifying an individual user of a mobile or wearable device. Individual and combinations of amino acids processed by biocatalytic cascades yield physical (optical or electronic) signals, providing a time-series of several outputs that, in their entirety, should suffice to authenticate a specific user based on standard statistical criteria. Initial results, motivated by biometrics, indicate that single amino acid levels can provide analog signals that vary according to the individual donor, albeit with limited resolution versus noise. However, some such assays offer digital separation (into well-defined ranges of values) according to groups such as age, biological sex, race, and physiological state of the individual. Multi-input biocatalytic cascades that handle several amino acid signals to yield a single digital-type output, as well as continuous-tracking time-series data rather than a single-instance sample, should enable active authentication at the level of an individual. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
A method for profiling biometric changes during disaccommodation.

Science.gov (United States)

Alderson, Alison; Davies, Leon N; Mallen, Edward A H; Sheppard, Amy L

2012-05-01

To demonstrate the application of low-coherence reflectometry to the study of biometric changes during disaccommodation responses in human eyes after cessation of a near task and to evaluate the effect of contact lenses on low-coherence reflectometry biometric measurements. Ocular biometric parameters of crystalline lens thickness (LT) and anterior chamber depth (ACD) were measured with the LenStar device during and immediately after a 5 D accommodative task in 10 participants. In a separate trial, accommodation responses were recorded with a Shin-Nippon WAM-5500 optometer in a subset of two participants. Biometric data were interleaved to form a profile of post-task anterior segment changes. In a further experiment, the effect of soft contact lenses on LenStar measurements was evaluated in 15 participants. In 10 adult participants, increased LT and reduced ACD was seen during the 5 D task. Post-task, during fixation of a 0 D target, a profile of the change in LT and ACD against time was observed. In the two participants with accommodation data (one a sufferer of nearwork-induced transient myopia and other a non-sufferer), the post-task changes in refraction compared favorably with the interleaved LenStar biometry data. The insertion of soft contact lenses did not have a significant effect on LenStar measures of ACD or LT (mean change: -0.007 mm, p = 0.265 and + 0.001 mm, p = 0.875, respectively). With the addition of a relatively simple stimulus modification, the LenStar instrument can be used to produce a profile of post-task changes in LT and ACD. The spatial and temporal resolution of the system is sufficient for the investigation of nearwork-induced transient myopia from a biometric viewpoint. LenStar measurements of ACD and LT remain valid after the fitting of soft contact lenses.
Biometric Authorization and Registration Systems and Methods

National Research Council Canada - National Science Library

Caulfield, H

2002-01-01

Biometric authorization and registration systems and methods are disclosed. In one embodiment, the system preferably comprises a firearm that includes a biometric authorization system, a plurality of training computers, and a server...

Biometrics IRB best practices and data protection

Science.gov (United States)

Boehnen, Christopher; Bolme, David; Flynn, Patrick

2015-05-01

The collection of data from human subjects for biometrics research in the United States requires the development of a data collection protocol that is reviewed by a Human Subjects Institutional Review Board (IRB). The IRB reviews the protocol for risks and approves it if it meets the criteria for approval specified in the relevant Federal regulations (45 CFR 46). Many other countries operate similar mechanisms for the protection of human subjects. IRBs review protocols for safety, confidentiality, and for minimization of risk associated with identity disclosure. Since biometric measurements are potentially identifying, IRB scrutiny of biometrics data collection protocols can be expected to be thorough. This paper discusses the intricacies of IRB best practices within the worldwide biometrics community. This is important because research decisions involving human subjects are made at a local level and do not set a precedent for decisions made by another IRB board. In many cases, what one board approves is not approved by another board, resulting in significant inconsistencies that prove detrimental to both researchers and human subjects. Furthermore, the level of biometrics expertise may be low on IRBs, which can contribute to the unevenness of reviews. This publication will suggest possible best practices for designing and seeking IRB approval for human subjects research involving biometrics measurements. The views expressed are the opinions of the authors.
Time Series Momentum

DEFF Research Database (Denmark)

Moskowitz, Tobias J.; Ooi, Yao Hua; Heje Pedersen, Lasse

2012-01-01

We document significant “time series momentum” in equity index, currency, commodity, and bond futures for each of the 58 liquid instruments we consider. We find persistence in returns for one to 12 months that partially reverses over longer horizons, consistent with sentiment theories of initial...... under-reaction and delayed over-reaction. A diversified portfolio of time series momentum strategies across all asset classes delivers substantial abnormal returns with little exposure to standard asset pricing factors and performs best during extreme markets. Examining the trading activities...
On Hunting Animals of the Biometric Menagerie for Online Signature.

Directory of Open Access Journals (Sweden)

Nesma Houmani

Full Text Available Individuals behave differently regarding to biometric authentication systems. This fact was formalized in the literature by the concept of Biometric Menagerie, defining and labeling user groups with animal names in order to reflect their characteristics with respect to biometric systems. This concept was illustrated for face, fingerprint, iris, and speech modalities. The present study extends the Biometric Menagerie to online signatures, by proposing a novel methodology that ties specific quality measures for signatures to categories of the Biometric Menagerie. Such measures are combined for retrieving automatically writer categories of the extended version of the Biometric Menagerie. Performance analysis with different types of classifiers shows the pertinence of our approach on the well-known MCYT-100 database.
On Hunting Animals of the Biometric Menagerie for Online Signature.

Science.gov (United States)

Houmani, Nesma; Garcia-Salicetti, Sonia

2016-01-01

Individuals behave differently regarding to biometric authentication systems. This fact was formalized in the literature by the concept of Biometric Menagerie, defining and labeling user groups with animal names in order to reflect their characteristics with respect to biometric systems. This concept was illustrated for face, fingerprint, iris, and speech modalities. The present study extends the Biometric Menagerie to online signatures, by proposing a novel methodology that ties specific quality measures for signatures to categories of the Biometric Menagerie. Such measures are combined for retrieving automatically writer categories of the extended version of the Biometric Menagerie. Performance analysis with different types of classifiers shows the pertinence of our approach on the well-known MCYT-100 database.
Autopoietic Theory as a Framework for Biometrics

Directory of Open Access Journals (Sweden)

Markus Schatten

2009-01-01

Full Text Available Autopoietic theory which represents a framework for describing complex non-linear and especially living systems is described in a context of biometric characteristics. It is argued that any living system by performing an internal process of reproducing its structural components yields physical biometric characteristics. Likewise any living system when structurally coupling to another (eventually allopoietic system yields a behavioral or psychological characteristic of the living system. It is shown that any system that can be considered as autopoietic can potentially be measured, authenticated and/or identified using adequate biometric methods, and thus biometrics is applicable to any autopoietic system: living beings, groups of living beings, social systems, organizations as well as information systems. In the end implications of such a conceptualization are discussed as well as possible applications.
International Work-Conference on Time Series

CERN Document Server

Pomares, Héctor

2016-01-01

This volume presents selected peer-reviewed contributions from The International Work-Conference on Time Series, ITISE 2015, held in Granada, Spain, July 1-3, 2015. It discusses topics in time series analysis and forecasting, advanced methods and online learning in time series, high-dimensional and complex/big data time series as well as forecasting in real problems. The International Work-Conferences on Time Series (ITISE) provide a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing the disciplines of computer science, mathematics, statistics and econometrics.
Carbon Nanotube Embedded Nanostructure for Biometrics.

Science.gov (United States)

Park, Juhyuk; Youn, Jae Ryoun; Song, Young Seok

2017-12-27

Low electric energy loss is a very important problem to minimize the decay of transferred energy intensity due to impedance mismatch. This issue has been dealt with by adding an impedance matching layer at the interface between two media. A strategy was proposed to improve the charge transfer from the human body to a biometric device by using an impedance matching nanostructure. Nanocomposite pattern arrays were fabricated with shape memory polymer and carbon nanotubes. The shape recovery ability of the nanopatterns enhanced durability and sustainability of the structure. It was found that the composite nanopatterns improved the current transfer by two times compared with the nonpatterned composite sample. The underlying mechanism of the enhanced charge transport was understood by carrying out a numerical simulation. We anticipate that this study can provide a new pathway for developing advanced biometric devices with high sensitivity to biological information.
75 FR 39323 - Amendment to the Biometric Visa Program

Science.gov (United States)

2010-07-08

... DEPARTMENT OF STATE [Public Notice: 7047] Amendment to the Biometric Visa Program AGENCY: Department of State. ACTION: Notice of Amendment to the Biometric Visa Program. This public notice announces an amendment to the Biometric Visa Program. Section 303 of the Enhanced Border Security and Visa...
Ethical considerations in implementing a biometric co-enrol- ment ...

African Journals Online (AJOL)

The biometrics co-enrolment prevention system (BCEPS) is a novel ... capture participant's identification details in real time was approved by the SAMRC Ethics Committee. ... for guidelines and standard operating procedures (SOPs) for the.
Multi-modal Behavioural Biometric Authentication for Mobile Devices

OpenAIRE

Saevanee , Hataichanok; Clarke , Nathan ,; Furnell , Steven ,

2012-01-01

Part 12: Authentication and Delegation; International audience; The potential advantages of behavioural biometrics are that they can be utilised in a transparent (non-intrusive) and continuous authentication system. However, individual biometric techniques are not suited to all users and scenarios. One way to increase the reliability of transparent and continuous authentication systems is create a multi-modal behavioural biometric authentication system. This research investigated three behavi...
Behavioural Biometrics for Multi-factor Authentication in Biomedicine

Czech Academy of Sciences Publication Activity Database

Schlenker, Anna; Šárek, M.

2012-01-01

Roč. 8, č. 5 (2012), s. 19-24 ISSN 1801-5603 Grant - others:GA MŠk(CZ) LM2010005; GA UK(CZ) SVV-2012-264513 Institutional support: RVO:67985807 Keywords : biometric s * anatomical-physiological biometric s * behavioural biometric s * multi-factor authentication * keystroke dynamics * mouse dynamics Subject RIV: IN - Informatics, Computer Science http://www.ejbi.org/img/ejbi/2012/5/Schlenker_en.pdf
Biometric recognition via texture features of eye movement trajectories in a visual searching task.

Science.gov (United States)

Li, Chunyong; Xue, Jiguo; Quan, Cheng; Yue, Jingwei; Zhang, Chenggang

2018-01-01

Biometric recognition technology based on eye-movement dynamics has been in development for more than ten years. Different visual tasks, feature extraction and feature recognition methods are proposed to improve the performance of eye movement biometric system. However, the correct identification and verification rates, especially in long-term experiments, as well as the effects of visual tasks and eye trackers' temporal and spatial resolution are still the foremost considerations in eye movement biometrics. With a focus on these issues, we proposed a new visual searching task for eye movement data collection and a new class of eye movement features for biometric recognition. In order to demonstrate the improvement of this visual searching task being used in eye movement biometrics, three other eye movement feature extraction methods were also tested on our eye movement datasets. Compared with the original results, all three methods yielded better results as expected. In addition, the biometric performance of these four feature extraction methods was also compared using the equal error rate (EER) and Rank-1 identification rate (Rank-1 IR), and the texture features introduced in this paper were ultimately shown to offer some advantages with regard to long-term stability and robustness over time and spatial precision. Finally, the results of different combinations of these methods with a score-level fusion method indicated that multi-biometric methods perform better in most cases.
Stochastic models for time series

CERN Document Server

Doukhan, Paul

2018-01-01

This book presents essential tools for modelling non-linear time series. The first part of the book describes the main standard tools of probability and statistics that directly apply to the time series context to obtain a wide range of modelling possibilities. Functional estimation and bootstrap are discussed, and stationarity is reviewed. The second part describes a number of tools from Gaussian chaos and proposes a tour of linear time series models. It goes on to address nonlinearity from polynomial or chaotic models for which explicit expansions are available, then turns to Markov and non-Markov linear models and discusses Bernoulli shifts time series models. Finally, the volume focuses on the limit theory, starting with the ergodic theorem, which is seen as the first step for statistics of time series. It defines the distributional range to obtain generic tools for limit theory under long or short-range dependences (LRD/SRD) and explains examples of LRD behaviours. More general techniques (central limit ...
Biometric Authentication Using the PPG: A Long-Term Feasibility Study

Directory of Open Access Journals (Sweden)

Jorge Sancho

2018-05-01

Full Text Available The photoplethysmogram (PPG is a biomedical signal that can be used to estimate volumetric blood flow changes in the peripheral circulation. During the past few years, several works have been published in order to assess the potential for PPGs to be used in biometric authentication systems, but results are inconclusive. In this paper we perform an analysis of the feasibility of using the PPG as a realistic biometric alternative in the long term. Several feature extractors (based on the time domain and the Karhunen–Loève transform and matching metrics (Manhattan and Euclidean distances have been tested using four different PPG databases (PRRB, MIMIC-II, Berry, and Nonin. We show that the false match rate (FMR and false non-match rate (FNMR values remain constant in different time instances for a selected threshold, which is essential for using the PPG for biometric authentication purposes. On the other hand, obtained equal error rate (EER values for signals recorded during the same session range from 1.0% for high-quality signals recorded in controlled conditions to 8% for those recorded in conditions closer to real-world scenarios. Moreover, in certain scenarios, EER values rise up to 23.2% for signals recorded over different days, signaling that performance degradation could take place with time.
Biometric Authentication Using the PPG: A Long-Term Feasibility Study.

Science.gov (United States)

Sancho, Jorge; Alesanco, Álvaro; García, José

2018-05-11

The photoplethysmogram (PPG) is a biomedical signal that can be used to estimate volumetric blood flow changes in the peripheral circulation. During the past few years, several works have been published in order to assess the potential for PPGs to be used in biometric authentication systems, but results are inconclusive. In this paper we perform an analysis of the feasibility of using the PPG as a realistic biometric alternative in the long term. Several feature extractors (based on the time domain and the Karhunen⁻Loève transform) and matching metrics (Manhattan and Euclidean distances) have been tested using four different PPG databases (PRRB, MIMIC-II, Berry, and Nonin). We show that the false match rate ( FMR ) and false non-match rate ( FNMR ) values remain constant in different time instances for a selected threshold, which is essential for using the PPG for biometric authentication purposes. On the other hand, obtained equal error rate (EER) values for signals recorded during the same session range from 1.0% for high-quality signals recorded in controlled conditions to 8% for those recorded in conditions closer to real-world scenarios. Moreover, in certain scenarios, EER values rise up to 23.2% for signals recorded over different days, signaling that performance degradation could take place with time.
Crop Biometric Maps: The Key to Prediction

Directory of Open Access Journals (Sweden)

Francisco Rovira-Más

2013-09-01

Full Text Available The sustainability of agricultural production in the twenty-first century, both in industrialized and developing countries, benefits from the integration of farm management with information technology such that individual plants, rows, or subfields may be endowed with a singular “identity.” This approach approximates the nature of agricultural processes to the engineering of industrial processes. In order to cope with the vast variability of nature and the uncertainties of agricultural production, the concept of crop biometrics is defined as the scientific analysis of agricultural observations confined to spaces of reduced dimensions and known position with the purpose of building prediction models. This article develops the idea of crop biometrics by setting its principles, discussing the selection and quantization of biometric traits, and analyzing the mathematical relationships among measured and predicted traits. Crop biometric maps were applied to the case of a wine-production vineyard, in which vegetation amount, relative altitude in the field, soil compaction, berry size, grape yield, juice pH, and grape sugar content were selected as biometric traits. The enological potential of grapes was assessed with a quality-index map defined as a combination of titratable acidity, sugar content, and must pH. Prediction models for yield and quality were developed for high and low resolution maps, showing the great potential of crop biometric maps as a strategic tool for vineyard growers as well as for crop managers in general, due to the wide versatility of the methodology proposed.
Crop biometric maps: the key to prediction.

Science.gov (United States)

Rovira-Más, Francisco; Sáiz-Rubio, Verónica

2013-09-23

The sustainability of agricultural production in the twenty-first century, both in industrialized and developing countries, benefits from the integration of farm management with information technology such that individual plants, rows, or subfields may be endowed with a singular "identity." This approach approximates the nature of agricultural processes to the engineering of industrial processes. In order to cope with the vast variability of nature and the uncertainties of agricultural production, the concept of crop biometrics is defined as the scientific analysis of agricultural observations confined to spaces of reduced dimensions and known position with the purpose of building prediction models. This article develops the idea of crop biometrics by setting its principles, discussing the selection and quantization of biometric traits, and analyzing the mathematical relationships among measured and predicted traits. Crop biometric maps were applied to the case of a wine-production vineyard, in which vegetation amount, relative altitude in the field, soil compaction, berry size, grape yield, juice pH, and grape sugar content were selected as biometric traits. The enological potential of grapes was assessed with a quality-index map defined as a combination of titratable acidity, sugar content, and must pH. Prediction models for yield and quality were developed for high and low resolution maps, showing the great potential of crop biometric maps as a strategic tool for vineyard growers as well as for crop managers in general, due to the wide versatility of the methodology proposed.
Graphical Data Analysis on the Circle: Wrap-Around Time Series Plots for (Interrupted) Time Series Designs.

Science.gov (United States)

Rodgers, Joseph Lee; Beasley, William Howard; Schuelke, Matthew

2014-01-01

Many data structures, particularly time series data, are naturally seasonal, cyclical, or otherwise circular. Past graphical methods for time series have focused on linear plots. In this article, we move graphical analysis onto the circle. We focus on 2 particular methods, one old and one new. Rose diagrams are circular histograms and can be produced in several different forms using the RRose software system. In addition, we propose, develop, illustrate, and provide software support for a new circular graphical method, called Wrap-Around Time Series Plots (WATS Plots), which is a graphical method useful to support time series analyses in general but in particular in relation to interrupted time series designs. We illustrate the use of WATS Plots with an interrupted time series design evaluating the effect of the Oklahoma City bombing on birthrates in Oklahoma County during the 10 years surrounding the bombing of the Murrah Building in Oklahoma City. We compare WATS Plots with linear time series representations and overlay them with smoothing and error bands. Each method is shown to have advantages in relation to the other; in our example, the WATS Plots more clearly show the existence and effect size of the fertility differential.
Trends in Biometric Health Indices Within an Employer-Sponsored Wellness Program With Outcome-Based Incentives.

Science.gov (United States)

Fu, Patricia Lin; Bradley, Kent L; Viswanathan, Sheila; Chan, June M; Stampfer, Meir

2016-07-01

To evaluate changes in employees' biometrics over time relative to outcome-based incentive thresholds. Retrospective cohort analysis of biometric screening participants (n = 26 388). Large employer primarily in Western United States. Office, retail, and distribution workforce. A voluntary outcome-based biometric screening program, incentivized with health insurance premium discounts. Body mass index (BMI), cholesterol, blood glucose, blood pressure, and nicotine. Followed were participants from their first year of participation, evaluating changes in measures. On average, participants who did not meet the incentive threshold at baseline decreased their BMI (1%), glucose (8%), blood pressure (systolic 9%, diastolic 8%), and total cholesterol (8%) by year 2 with improvements generally sustained or continued during each additional year of participation. On average, individuals at high health risk who participated in a financially incentivized biometric assessment program improved their health indices over time. Further research is needed to understand key determinants that drive health improvement indicated here. © The Author(s) 2016.
Securing information using optically generated biometric keys

Science.gov (United States)

Verma, Gaurav; Sinha, Aloka

2016-11-01

In this paper, we present a new technique to obtain biometric keys by using the fingerprint of a person for an optical image encryption system. The key generation scheme uses the fingerprint biometric information in terms of the amplitude mask (AM) and the phase mask (PM) of the reconstructed fingerprint image that is implemented using the digital holographic technique. Statistical tests have been conducted to check the randomness of the fingerprint PM key that enables its usage as an image encryption key. To explore the utility of the generated biometric keys, an optical image encryption system has been further demonstrated based on the phase retrieval algorithm and the double random phase encoding scheme in which keys for the encryption are used as the AM and the PM key. The advantage associated with the proposed scheme is that the biometric keys’ retrieval requires the simultaneous presence of the fingerprint hologram and the correct knowledge of the reconstruction parameters at the decryption stage, which not only verifies the authenticity of the person but also protects the valuable fingerprint biometric features of the keys. Numerical results are carried out to prove the feasibility and the effectiveness of the proposed encryption system.

BIOMETRIC AUTHENTICATION SYSTEM USING RPI

OpenAIRE

Fatema A. Shaikh*; Prof.S.O.Rajankar

2016-01-01

A biometric authentication system acquires biometric sample such as fingerprint. The fingerprint signifies physiological features of an individual.This is a system which maintains the attendance records of students automatically. In this designing of an efficient module that comprises of a fingerprint sensor to manage the attendance records of students. This module enrolls the student’s as well as staff’s fingerprints. This enrolling is a onetime process and their fingerprints will be stored...
Can visual evoked potentials be used in biometric identification?

Science.gov (United States)

Power, Alan J; Lalor, Edmund C; Reilly, Richard B

2006-01-01

Due to known differences in the anatomical structure of the visual pathways and generators in different individuals, the use of visual evoked potentials offers the possibility of an alternative to existing biometrics methods. A study based on visual evoked potentials from 13 individuals was carried out to assess the best combination of temporal, spectral and AR modeling features to realize a robust biometric. From the results it can be concluded that visual evoked potentials show considerable biometric qualities, with classification accuracies reaching a high of 86.54% and that a specific temporal and spectral combination was found to be optimal. Based on these results the visual evoked potential may be a useful tool in biometric identification when used in conjunction with more established biometric methods.
Quantum Biometrics with Retinal Photon Counting

Science.gov (United States)

Loulakis, M.; Blatsios, G.; Vrettou, C. S.; Kominis, I. K.

2017-10-01

It is known that the eye's scotopic photodetectors, rhodopsin molecules, and their associated phototransduction mechanism leading to light perception, are efficient single-photon counters. We here use the photon-counting principles of human rod vision to propose a secure quantum biometric identification based on the quantum-statistical properties of retinal photon detection. The photon path along the human eye until its detection by rod cells is modeled as a filter having a specific transmission coefficient. Precisely determining its value from the photodetection statistics registered by the conscious observer is a quantum parameter estimation problem that leads to a quantum secure identification method. The probabilities for false-positive and false-negative identification of this biometric technique can readily approach 10-10 and 10-4, respectively. The security of the biometric method can be further quantified by the physics of quantum measurements. An impostor must be able to perform quantum thermometry and quantum magnetometry with energy resolution better than 10-9ℏ , in order to foil the device by noninvasively monitoring the biometric activity of a user.
Privacy leakage in binary biometric systems : from gaussian to binary data

NARCIS (Netherlands)

Ignatenko, T.; Willems, F.M.J.; Campisi, P.

2013-01-01

In this chapter we investigate biometric key-binding systems for i.i.d. Gaussian biometric sources. In these systems two terminals observe two correlated biometric sequences. Moreover, a secret key, which is independent of the biometric sequences, is selected at the first terminal. The first
Haar-like Rectangular Features for Biometric Recognition

DEFF Research Database (Denmark)

Nasrollahi, Kamal; Moeslund, Thomas B.; Rashidi, Maryam

2013-01-01

Developing a reliable, fast, and robust biometric recognition system is still a challenging task. This is because the inputs to these systems can be noisy, occluded, poorly illuminated, rotated, and of very low-resolutions. This paper proposes a probabilistic classifier using Haar-like features......, which mostly have been used for detection, for biometric recognition. The proposed system has been tested for three different biometrics: ear, iris, and hand vein patterns and it is shown that it is robust against most of the mentioned degradations and it outperforms state-of-the-art systems...
Iris recognition as a biometric method after cataract surgery.

Science.gov (United States)

Roizenblatt, Roberto; Schor, Paulo; Dante, Fabio; Roizenblatt, Jaime; Belfort, Rubens

2004-01-28

Biometric methods are security technologies, which use human characteristics for personal identification. Iris recognition systems use iris textures as unique identifiers. This paper presents an analysis of the verification of iris identities after intra-ocular procedures, when individuals were enrolled before the surgery. Fifty-five eyes from fifty-five patients had their irises enrolled before a cataract surgery was performed. They had their irises verified three times before and three times after the procedure, and the Hamming (mathematical) distance of each identification trial was determined, in a controlled ideal biometric environment. The mathematical difference between the iris code before and after the surgery was also compared to a subjective evaluation of the iris anatomy alteration by an experienced surgeon. A correlation between visible subjective iris texture alteration and mathematical difference was verified. We found only six cases in which the eye was no more recognizable, but these eyes were later reenrolled. The main anatomical changes that were found in the new impostor eyes are described. Cataract surgeries change iris textures in such a way that iris recognition systems, which perform mathematical comparisons of textural biometric features, are able to detect these changes and sometimes even discard a pre-enrolled iris considering it an impostor. In our study, re-enrollment proved to be a feasible procedure.
Unobtrusive Multimodal Biometric Authentication: The HUMABIO Project Concept

Directory of Open Access Journals (Sweden)

Evangelos Bekiaris

2008-03-01

Full Text Available Human Monitoring and Authentication using Biodynamic Indicators and Behavioural Analysis (HUMABIO (2007 is an EU Specific Targeted Research Project (STREP where new types of biometrics are combined with state of the art sensorial technologies in order to enhance security in a wide spectrum of applications. The project aims to develop a modular, robust, multimodal biometrics security authentication and monitoring system which utilizes a biodynamic physiological profile, unique for each individual, and advancements of the state-of-the art in behavioural and other biometrics, such as face, speech, gait recognition, and seat-based anthropometrics. Several shortcomings in biometric authentication will be addressed in the course of HUMABIO which will provide the basis for improving existing sensors, develop new algorithms, and design applications, towards creating new, unobtrusive biometric authentication procedures in security sensitive, controlled environments. This paper presents the concept of this project, describes its unobtrusive authentication demonstrator, and reports some preliminary results.
A survey of keystroke dynamics biometrics.

Science.gov (United States)

Teh, Pin Shen; Teoh, Andrew Beng Jin; Yue, Shigang

2013-01-01

Research on keystroke dynamics biometrics has been increasing, especially in the last decade. The main motivation behind this effort is due to the fact that keystroke dynamics biometrics is economical and can be easily integrated into the existing computer security systems with minimal alteration and user intervention. Numerous studies have been conducted in terms of data acquisition devices, feature representations, classification methods, experimental protocols, and evaluations. However, an up-to-date extensive survey and evaluation is not yet available. The objective of this paper is to provide an insightful survey and comparison on keystroke dynamics biometrics research performed throughout the last three decades, as well as offering suggestions and possible future research directions.
Towards the Security Evaluation of Biometric Authentication Systems

OpenAIRE

El-Abed , Mohamad; Giot , Romain; Hemery , Baptiste; Rosenberger , Christophe; Schwartzmann , Jean-Jacques

2011-01-01

International audience; Despite the obvious advantages of biometric authentication systems over traditional security ones (based on tokens or passwords), they are vulnerable to attacks which may considerably decrease their security. In order to contribute in resolving such problematic, we propose a modality-independent evaluation methodology for the security evaluation of biometric systems. It is based on the use of a database of common threats and vulnerabilities of biometric systems, and th...
Secret-key rates and privacy leakage in biometric systems

NARCIS (Netherlands)

Ignatenko, T.

2009-01-01

In this thesis both the generation of secret keys from biometric data and the binding of secret keys to biometric data are investigated. These secret keys can be used to regulate access to sensitive data, services, and environments. In a biometric secrecy system a secret key is generated or chosen
Time Series with Long Memory

OpenAIRE

西埜, 晴久

2004-01-01

The paper investigates an application of long-memory processes to economic time series. We show properties of long-memory processes, which are motivated to model a long-memory phenomenon in economic time series. An FARIMA model is described as an example of long-memory model in statistical terms. The paper explains basic limit theorems and estimation methods for long-memory processes in order to apply long-memory models to economic time series.
Societal and ethical implications of anti-spoofing technologies in biometrics.

Science.gov (United States)

Rebera, Andrew P; Bonfanti, Matteo E; Venier, Silvia

2014-03-01

Biometric identification is thought to be less vulnerable to fraud and forgery than are traditional forms of identification. However biometric identification is not without vulnerabilities. In a 'spoofing attack' an artificial replica of an individual's biometric trait is used to induce a system to falsely infer that individual's presence. Techniques such as liveness-detection and multi-modality, as well as the development of new and emerging modalities, are intended to secure biometric identification systems against such threats. Unlike biometrics in general, the societal and ethical issues raised by spoofing and anti-spoofing techniques have not received much attention. This paper examines these issues.
Visibility Graph Based Time Series Analysis.

Science.gov (United States)

Stephen, Mutua; Gu, Changgui; Yang, Huijie

2015-01-01

Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it's microscopic and macroscopic behaviors. However, most proposed approaches lead to the construction of static networks consequently providing limited information on evolutionary behaviors. In the present paper we propose a method called visibility graph based time series analysis, in which series segments are mapped to visibility graphs as being descriptions of the corresponding states and the successively occurring states are linked. This procedure converts a time series to a temporal network and at the same time a network of networks. Findings from empirical records for stock markets in USA (S&P500 and Nasdaq) and artificial series generated by means of fractional Gaussian motions show that the method can provide us rich information benefiting short-term and long-term predictions. Theoretically, we propose a method to investigate time series from the viewpoint of network of networks.
Visibility Graph Based Time Series Analysis.

Directory of Open Access Journals (Sweden)

Mutua Stephen

Full Text Available Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it's microscopic and macroscopic behaviors. However, most proposed approaches lead to the construction of static networks consequently providing limited information on evolutionary behaviors. In the present paper we propose a method called visibility graph based time series analysis, in which series segments are mapped to visibility graphs as being descriptions of the corresponding states and the successively occurring states are linked. This procedure converts a time series to a temporal network and at the same time a network of networks. Findings from empirical records for stock markets in USA (S&P500 and Nasdaq and artificial series generated by means of fractional Gaussian motions show that the method can provide us rich information benefiting short-term and long-term predictions. Theoretically, we propose a method to investigate time series from the viewpoint of network of networks.
Four Machine Learning Algorithms for Biometrics Fusion: A Comparative Study

Directory of Open Access Journals (Sweden)

I. G. Damousis

2012-01-01

Full Text Available We examine the efficiency of four machine learning algorithms for the fusion of several biometrics modalities to create a multimodal biometrics security system. The algorithms examined are Gaussian Mixture Models (GMMs, Artificial Neural Networks (ANNs, Fuzzy Expert Systems (FESs, and Support Vector Machines (SVMs. The fusion of biometrics leads to security systems that exhibit higher recognition rates and lower false alarms compared to unimodal biometric security systems. Supervised learning was carried out using a number of patterns from a well-known benchmark biometrics database, and the validation/testing took place with patterns from the same database which were not included in the training dataset. The comparison of the algorithms reveals that the biometrics fusion system is superior to the original unimodal systems and also other fusion schemes found in the literature.
A robust probabilistic collaborative representation based classification for multimodal biometrics

Science.gov (United States)

Zhang, Jing; Liu, Huanxi; Ding, Derui; Xiao, Jianli

2018-04-01

Most of the traditional biometric recognition systems perform recognition with a single biometric indicator. These systems have suffered noisy data, interclass variations, unacceptable error rates, forged identity, and so on. Due to these inherent problems, it is not valid that many researchers attempt to enhance the performance of unimodal biometric systems with single features. Thus, multimodal biometrics is investigated to reduce some of these defects. This paper proposes a new multimodal biometric recognition approach by fused faces and fingerprints. For more recognizable features, the proposed method extracts block local binary pattern features for all modalities, and then combines them into a single framework. For better classification, it employs the robust probabilistic collaborative representation based classifier to recognize individuals. Experimental results indicate that the proposed method has improved the recognition accuracy compared to the unimodal biometrics.
Multimodal biometric approach for cancelable face template generation

Science.gov (United States)

Paul, Padma Polash; Gavrilova, Marina

2012-06-01

Due to the rapid growth of biometric technology, template protection becomes crucial to secure integrity of the biometric security system and prevent unauthorized access. Cancelable biometrics is emerging as one of the best solutions to secure the biometric identification and verification system. We present a novel technique for robust cancelable template generation algorithm that takes advantage of the multimodal biometric using feature level fusion. Feature level fusion of different facial features is applied to generate the cancelable template. A proposed algorithm based on the multi-fold random projection and fuzzy communication scheme is used for this purpose. In cancelable template generation, one of the main difficulties is keeping interclass variance of the feature. We have found that interclass variations of the features that are lost during multi fold random projection can be recovered using fusion of different feature subsets and projecting in a new feature domain. Applying the multimodal technique in feature level, we enhance the interclass variability hence improving the performance of the system. We have tested the system for classifier fusion for different feature subset and different cancelable template fusion. Experiments have shown that cancelable template improves the performance of the biometric system compared with the original template.
Corneal topography measurements for biometric applications

Science.gov (United States)

Lewis, Nathan D.

The term biometrics is used to describe the process of analyzing biological and behavioral traits that are unique to an individual in order to confirm or determine his or her identity. Many biometric modalities are currently being researched and implemented including, fingerprints, hand and facial geometry, iris recognition, vein structure recognition, gait, voice recognition, etc... This project explores the possibility of using corneal topography measurements as a trait for biometric identification. Two new corneal topographers were developed for this study. The first was designed to function as an operator-free device that will allow a user to approach the device and have his or her corneal topography measured. Human subject topography data were collected with this device and compared to measurements made with the commercially available Keratron Piccolo topographer (Optikon, Rome, Italy). A third topographer that departs from the standard Placido disk technology allows for arbitrary pattern illumination through the use of LCD monitors. This topographer was built and tested to be used in future research studies. Topography data was collected from 59 subjects and modeled using Zernike polynomials, which provide for a simple method of compressing topography data and comparing one topographical measurement with a database for biometric identification. The data were analyzed to determine the biometric error rates associated with corneal topography measurements. Reasonably accurate results, between three to eight percent simultaneous false match and false non-match rates, were achieved.
Secure Method for Biometric-Based Recognition with Integrated Cryptographic Functions

OpenAIRE

Chiou, Shin-Yan

2013-01-01

Biometric systems refer to biometric technologies which can be used to achieve authentication. Unlike cryptography-based technologies, the ratio for certification in biometric systems needs not to achieve 100% accuracy. However, biometric data can only be directly compared through proximal access to the scanning device and cannot be combined with cryptographic techniques. Moreover, repeated use, improper storage, or transmission leaks may compromise security. Prior studies have attempted to c...
Advances in biometrics for secure human authentication and recognition

CERN Document Server

Kisku, Dakshina Ranjan; Sing, Jamuna Kanta

2013-01-01

GENERAL BIOMETRICSSecurity and Reliability Assessment for Biometric Systems; Gayatri MirajkarReview of Human Recognition Based on Retinal Images; Amin DehghaniADVANCED TOPICS IN BIOMETRICSVisual Speech as Behavioral Biometric; Preety Singh, Vijay Laxmi, and Manoj Singh GaurHuman Gait Signature for Biometric Authentication; Vijay JohnHand-Based Biometric for Personal Identification Using Correlation Filter Classifier; Mohammed Saigaa , Abdallah Meraoumia , Salim Chitroub, and Ahmed BouridaneOn Deciding the Dynamic Periocular Boundary for Human Recognition; Sambit Bakshi , Pankaj Kumar Sa, and Banshidhar MajhiRetention of Electrocardiogram Features Insignificantly Devalorized as an Effect of Watermarking for a Multimodal Biometric Authentication System; Nilanjan Dey, Bijurika Nandi, Poulami Das, Achintya Das, and Sheli Sinha ChaudhuriFacial Feature Point Extraction for Object Identification Using Discrete Contourlet Transform and Principal Component Analysis; N. G. Chitaliya and A. I. TrivediCASE STUDIES AND LA...

On humanitarian refugee biometrics and new forms of intervention

DEFF Research Database (Denmark)

Jacobsen, Katja Lindskov

2017-01-01

This article traces a development from UNHCR's initial use of biometrics in a few pilot projects (early/mid-2000s), to the emergence of a UNHCR policy where biometric registration is considered a "strategic decision". Next it engages key insights from current debates about 'materiality' and agentic...... capacity in combination with current debates about new forms of intervention. Finally, these insights are combined into a framework through which the last part of the article engages critically with this development of humanitarian refugee biometrics by posing the following question: how does an approach...... biometric refugee data, has affected the relationship between UNHCR, donor states, host states and refugees, the article shows how UNHCR's trialling of new biometric technologies, combined with actual and potential data-sharing practices, has advanced the technology's performance as well as its...
Forgery quality and its implications for behavioral biometric security.

Science.gov (United States)

Ballard, Lucas; Lopresti, Daniel; Monrose, Fabian

2007-10-01

Biometric security is a topic of rapidly growing importance in the areas of user authentication and cryptographic key generation. In this paper, we describe our steps toward developing evaluation methodologies for behavioral biometrics that take into account threat models that have been largely ignored. We argue that the pervasive assumption that forgers are minimally motivated (or, even worse, naive) is too optimistic and even dangerous. Taking handwriting as a case in point, we show through a series of experiments that some users are significantly better forgers than others, that such forgers can be trained in a relatively straightforward fashion to pose an even greater threat, that certain users are easy targets for forgers, and that most humans are a relatively poor judge of handwriting authenticity, and hence, their unaided instincts cannot be trusted. Additionally, to overcome current labor-intensive hurdles in performing more accurate assessments of system security, we present a generative attack model based on concatenative synthesis that can provide a rapid indication of the security afforded by the system. We show that our generative attacks match or exceed the effectiveness of forgeries rendered by the skilled humans we have encountered.
Robust and Secure Watermarking Using Sparse Information of Watermark for Biometric Data Protection

Directory of Open Access Journals (Sweden)

Rohit M Thanki

2016-08-01

Full Text Available Biometric based human authentication system is used for security purpose in many organizations in the present world. This biometric authentication system has several vulnerable points. Two of vulnerable points are protection of biometric templates at system database and protection of biometric templates at communication channel between two modules of biometric authentication systems. In this paper proposed a robust watermarking scheme using the sparse information of watermark biometric to secure vulnerable point like protection of biometric templates at the communication channel of biometric authentication systems. A compressive sensing theory procedure is used for generation of sparse information on watermark biometric data using detail wavelet coefficients. Then sparse information of watermark biometric data is embedded into DCT coefficients of host biometric data. This proposed scheme is robust to common signal processing and geometric attacks like JPEG compression, adding noise, filtering, and cropping, histogram equalization. This proposed scheme has more advantages and high quality measures compared to existing schemes in the literature.
Controlling Leakage of Biometric Information using Dithering

NARCIS (Netherlands)

Buhan, I.R.; Doumen, J.M.; Hartel, Pieter H.; Buhan, I.R.; Doumen, J.M.; Hartel, P.H.

Fuzzy extractors allow cryptographic keys to be generated from noisy, non-uniform biometric data. Fuzzy extractors can be used to authenticate a user to a server without storing her biometric data directly. However, in the Information Theoretic sense fuzzy extractors will leak information about the
Joint Sparse Representation for Robust Multimodal Biometrics Recognition

Science.gov (United States)

2014-01-01

Biometrics with error term Finger 1 Finger 2 Finger 3 Finger ...Individual Biometrics without error term Finger 1 Finger 2 Finger 3 Finger 4 Iris 1 Iris 2 (a) (b) 20 40 60 80 100 120 140 160 180 200 220 60 65 70...75 80 85 90 95 Rank C um ul at iv e R ec og ni tio n R at e (% ) CMC Curve for Individual Biometrics using SLR Finger 1 Finger 2
Network structure of multivariate time series.

Science.gov (United States)

Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

2015-10-21

Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail.
Biometrics in support of special forces medical operations.

Science.gov (United States)

Kershner, Michael R

2012-01-01

Recommendations on ways in which the ODA can leverage biometrics in medical operations to improve their security, improve relations with indigenous personnel, and contribute to the larger theater biometrics program. 2012.
Biometric Secured Result Processing Software For Nigerian Tertiary Institutions

Directory of Open Access Journals (Sweden)

Oladipo Oluwasegun

2015-08-01

Full Text Available Abstract One of the challenges facing result processing in Nigerian tertiary institutions is the problem of insecurity. Untraceable changes are made to students result and this result to various disasters such as innocent people losing their jobs since their innocence cannot be proven. Biometric based systems operate on behavioral and physiological biometric data to identify a person and grant required access to a user. Physiological characteristics such as fingerprint remains unchanged throughout an individuals life time and thus it can serve as a viable means of identifying and authenticating users who are to access a system. In this study fingerprint biometric based result processing software is developed to ensure that users are well authenticated and are made to see only what they are pre-configured to see and work with. The fingerprint authentication system was developed using visual basic.net. Staff fingerprints were enrolled into the system to form a biometric template which the system validates against at every login attempt on the result processing software. The digital personal one touch ID sdk and other libraries were used in developing the authentication system. The result processing software also ensures that all write transactions to the database are confirmed and identified by forcing another biometric authentication at the point of making a write request to the web server and associated database. This ensures that the exact person initiating the transaction was the same user who logged in to the application. The users identified at login and various confirmation milestones set for write transactions are logged into a table for future reference and audit trail. Conclusively the developed system has helped to eradicate the problem of user impersonation by ensuring only authorized users are made to access the software and in-turn participate in result processing activities.
What marketing scholars should know about time series analysis : time series applications in marketing

NARCIS (Netherlands)

Horváth, Csilla; Kornelis, Marcel; Leeflang, Peter S.H.

2002-01-01

In this review, we give a comprehensive summary of time series techniques in marketing, and discuss a variety of time series analysis (TSA) techniques and models. We classify them in the sets (i) univariate TSA, (ii) multivariate TSA, and (iii) multiple TSA. We provide relevant marketing
Realistic Measurement of Student Attendance in LMS Using Biometrics

Directory of Open Access Journals (Sweden)

Elisardo Gonzalez-Agulla

2010-10-01

Full Text Available In this paper we propose a solution to obtain useful and reliable student session logs in a Learning Management System (LMS combining current logs with biometrics-based logs that show the student behaviour during the whole learning session. The aims of our solution are to guarantee that the online student is who he/she claims to be, and also to know exactly how much time he/she spends in front of the computer reading each LMS content. Even when the proposed solution does not completely avoid cheating, the use of biometric data during authentication and face tracking provides additional help to validate student performance during learning sessions. In this way it is possible to improve security for specific contents, to gain feedback of the student effort and to check the actual time spent in learning.
Are Haar-like Rectangular Features for Biometric Recognition Reducible?

DEFF Research Database (Denmark)

Nasrollahi, Kamal; Moeslund, Thomas B.

2013-01-01

Biometric recognition is still a very difficult task in real-world scenarios wherein unforeseen changes in degradations factors like noise, occlusion, blurriness and illumination can drastically affect the extracted features from the biometric signals. Very recently Haar-like rectangular features...... which have usually been used for object detection were introduced for biometric recognition resulting in systems that are robust against most of the mentioned degradations [9]. The problem with these features is that one can define many different such features for a given biometric signal...... and it is not clear whether all of these features are required for the actual recognition or not. This is exactly what we are dealing with in this paper: How can an initial set of Haar-like rectangular features, that have been used for biometric recognition, be reduced to a set of most influential features...
Semiparametric Copula Models for Biometric Score Level

NARCIS (Netherlands)

Caselli, M.

2016-01-01

In biometric recognition systems, biometric samples (images of faces, finger- prints, voices, gaits, etc.) of people are compared and classifiers (matchers) indicate the level of similarity between any pair of samples by a score. If two samples of the same person are compared, a genuine score is
Soft biometrics in conjunction with optics based biohashing

Science.gov (United States)

Saini, Nirmala; Sinha, Aloka

2011-02-01

Biometric systems are gaining importance because of increased reliability for authentication and identification. A biometric recognition technique has been proposed earlier, in which biohashing code has been generated by using a joint transform correlator. The main drawback of the base biohashing method is the low performance of the technique when an "impostor" steals the pseudo-random numbers of the genuine and tries to authenticate as genuine. In the proposed technique, soft biometrics of the same person has been used to improve the discrimination between the genuine and the impostor populations. The soft biometrics are those characteristics that provide some information about the individual, but lack the distinctiveness and permanence to sufficiently differentiate between any two individuals. In the enrolment process, biohash code of the target face images has been integrated with the different soft biometrics of the same person. The obtained code has been stored for verification. In the verification process, biohash code of the face image to be verified is again diffused with the soft biometric of the person. The obtained code is matched with the stored code of the target. The receiving operating characteristic (ROC) curve and the equal error rate (EER) have been used to evaluate the performance of the technique. A detailed study has been carried out to find out the optimum values of the weighting factor for the diffusion process.
Multimodal biometric system using rank-level fusion approach.

Science.gov (United States)

Monwar, Md Maruf; Gavrilova, Marina L

2009-08-01

In many real-world applications, unimodal biometric systems often face significant limitations due to sensitivity to noise, intraclass variability, data quality, nonuniversality, and other factors. Attempting to improve the performance of individual matchers in such situations may not prove to be highly effective. Multibiometric systems seek to alleviate some of these problems by providing multiple pieces of evidence of the same identity. These systems help achieve an increase in performance that may not be possible using a single-biometric indicator. This paper presents an effective fusion scheme that combines information presented by multiple domain experts based on the rank-level fusion integration method. The developed multimodal biometric system possesses a number of unique qualities, starting from utilizing principal component analysis and Fisher's linear discriminant methods for individual matchers (face, ear, and signature) identity authentication and utilizing the novel rank-level fusion method in order to consolidate the results obtained from different biometric matchers. The ranks of individual matchers are combined using the highest rank, Borda count, and logistic regression approaches. The results indicate that fusion of individual modalities can improve the overall performance of the biometric system, even in the presence of low quality data. Insights on multibiometric design using rank-level fusion and its performance on a variety of biometric databases are discussed in the concluding section.
Practical security and privacy attacks against biometric hashing using sparse recovery

Science.gov (United States)

Topcu, Berkay; Karabat, Cagatay; Azadmanesh, Matin; Erdogan, Hakan

2016-12-01

Biometric hashing is a cancelable biometric verification method that has received research interest recently. This method can be considered as a two-factor authentication method which combines a personal password (or secret key) with a biometric to obtain a secure binary template which is used for authentication. We present novel practical security and privacy attacks against biometric hashing when the attacker is assumed to know the user's password in order to quantify the additional protection due to biometrics when the password is compromised. We present four methods that can reconstruct a biometric feature and/or the image from a hash and one method which can find the closest biometric data (i.e., face image) from a database. Two of the reconstruction methods are based on 1-bit compressed sensing signal reconstruction for which the data acquisition scenario is very similar to biometric hashing. Previous literature introduced simple attack methods, but we show that we can achieve higher level of security threats using compressed sensing recovery techniques. In addition, we present privacy attacks which reconstruct a biometric image which resembles the original image. We quantify the performance of the attacks using detection error tradeoff curves and equal error rates under advanced attack scenarios. We show that conventional biometric hashing methods suffer from high security and privacy leaks under practical attacks, and we believe more advanced hash generation methods are necessary to avoid these attacks.
Body, biometrics and identity.

Science.gov (United States)

Mordini, Emilio; Massari, Sonia

2008-11-01

According to a popular aphorism, biometrics are turning the human body into a passport or a password. As usual, aphorisms say more than they intend. Taking the dictum seriously, we would be two: ourself and our body. Who are we, if we are not our body? And what is our body without us? The endless history of identification systems teaches that identification is not a trivial fact but always involves a web of economic interests, political relations, symbolic networks, narratives and meanings. Certainly there are reasons for the ethical and political concerns surrounding biometrics but these reasons are probably quite different from those usually alleged.
Data mining in time series databases

CERN Document Server

Kandel, Abraham; Bunke, Horst

2004-01-01

Adding the time dimension to real-world databases produces Time SeriesDatabases (TSDB) and introduces new aspects and difficulties to datamining and knowledge discovery. This book covers the state-of-the-artmethodology for mining time series databases. The novel data miningmethods presented in the book include techniques for efficientsegmentation, indexing, and classification of noisy and dynamic timeseries. A graph-based method for anomaly detection in time series isdescribed and the book also studies the implications of a novel andpotentially useful representation of time series as strings. Theproblem of detecting changes in data mining models that are inducedfrom temporal databases is additionally discussed.
Models for dependent time series

CERN Document Server

Tunnicliffe Wilson, Granville; Haywood, John

2015-01-01

Models for Dependent Time Series addresses the issues that arise and the methodology that can be applied when the dependence between time series is described and modeled. Whether you work in the economic, physical, or life sciences, the book shows you how to draw meaningful, applicable, and statistically valid conclusions from multivariate (or vector) time series data.The first four chapters discuss the two main pillars of the subject that have been developed over the last 60 years: vector autoregressive modeling and multivariate spectral analysis. These chapters provide the foundational mater
Dual watermarking technique with multiple biometric watermarks

Indian Academy of Sciences (India)

affect the visual quality of the original art. On the contrary, removable visible watermarking .... Significant motivation for using biometric features such as face, voice and signature as a watermark is that face and ... These are the major reasons which motivated us to propose multimodal biometric watermarking. When the ...
Robust and Secure Watermarking Using Sparse Information of Watermark for Biometric Data Protection

OpenAIRE

Rohit M Thanki; Ved Vyas Dwivedi; Komal Borisagar

2016-01-01

Biometric based human authentication system is used for security purpose in many organizations in the present world. This biometric authentication system has several vulnerable points. Two of vulnerable points are protection of biometric templates at system database and protection of biometric templates at communication channel between two modules of biometric authentication systems. In this paper proposed a robust watermarking scheme using the sparse information of watermark biometric to sec...

Visual time series analysis

DEFF Research Database (Denmark)

Fischer, Paul; Hilbert, Astrid

2012-01-01

We introduce a platform which supplies an easy-to-handle, interactive, extendable, and fast analysis tool for time series analysis. In contrast to other software suits like Maple, Matlab, or R, which use a command-line-like interface and where the user has to memorize/look-up the appropriate...... commands, our application is select-and-click-driven. It allows to derive many different sequences of deviations for a given time series and to visualize them in different ways in order to judge their expressive power and to reuse the procedure found. For many transformations or model-ts, the user may...... choose between manual and automated parameter selection. The user can dene new transformations and add them to the system. The application contains efficient implementations of advanced and recent techniques for time series analysis including techniques related to extreme value analysis and filtering...
Correlation of iris biometrics and DNA

DEFF Research Database (Denmark)

Harder, Stine; Clemmensen, Line Katrine Harder; Dahl, Anders Bjorholm

2013-01-01

The presented work concerns prediction of complex human phenotypes from genotypes. We were interested in correlating iris color and texture with DNA. Our data consist of 212 eye images along with DNA: 32 single-nucleotide polymorphisms (SNPs). We used two types of biometrics to describe the eye...... images: One for iris color and one for iris texture. Both biometrics were high dimensional and a sparse principle component analysis (SPCA) reduced the dimensions and resulted in a representation of data with good interpretability. The correlations between the sparse principal components (SPCs......) and the 32 SNPs were found using a canonical correlation analysis (CCA). The result was a single significant canonical correlation (CC) for both biometrics. Each CC comprised two correlated canonical variables, consisting of a linear combination of SPCs and a linear combination of SNPs, respectively...
Iris recognition as a biometric method after cataract surgery

Directory of Open Access Journals (Sweden)

Roizenblatt Jaime

2004-01-01

Full Text Available Abstract Background Biometric methods are security technologies, which use human characteristics for personal identification. Iris recognition systems use iris textures as unique identifiers. This paper presents an analysis of the verification of iris identities after intra-ocular procedures, when individuals were enrolled before the surgery. Methods Fifty-five eyes from fifty-five patients had their irises enrolled before a cataract surgery was performed. They had their irises verified three times before and three times after the procedure, and the Hamming (mathematical distance of each identification trial was determined, in a controlled ideal biometric environment. The mathematical difference between the iris code before and after the surgery was also compared to a subjective evaluation of the iris anatomy alteration by an experienced surgeon. Results A correlation between visible subjective iris texture alteration and mathematical difference was verified. We found only six cases in which the eye was no more recognizable, but these eyes were later reenrolled. The main anatomical changes that were found in the new impostor eyes are described. Conclusions Cataract surgeries change iris textures in such a way that iris recognition systems, which perform mathematical comparisons of textural biometric features, are able to detect these changes and sometimes even discard a pre-enrolled iris considering it an impostor. In our study, re-enrollment proved to be a feasible procedure.
Unobtrusive behavioral and activity-related multimodal biometrics: The ACTIBIO Authentication concept.

Science.gov (United States)

Drosou, A; Ioannidis, D; Moustakas, K; Tzovaras, D

2011-03-01

Unobtrusive Authentication Using ACTIvity-Related and Soft BIOmetrics (ACTIBIO) is an EU Specific Targeted Research Project (STREP) where new types of biometrics are combined with state-of-the-art unobtrusive technologies in order to enhance security in a wide spectrum of applications. The project aims to develop a modular, robust, multimodal biometrics security authentication and monitoring system, which uses a biodynamic physiological profile, unique for each individual, and advancements of the state of the art in unobtrusive behavioral and other biometrics, such as face, gait recognition, and seat-based anthropometrics. Several shortcomings of existing biometric recognition systems are addressed within this project, which have helped in improving existing sensors, in developing new algorithms, and in designing applications, towards creating new, unobtrusive, biometric authentication procedures in security-sensitive, Ambient Intelligence environments. This paper presents the concept of the ACTIBIO project and describes its unobtrusive authentication demonstrator in a real scenario by focusing on the vision-based biometric recognition modalities.
Unobtrusive Behavioral and Activity-Related Multimodal Biometrics: The ACTIBIO Authentication Concept

Directory of Open Access Journals (Sweden)

A. Drosou

2011-01-01

Full Text Available Unobtrusive Authentication Using ACTIvity-Related and Soft BIOmetrics (ACTIBIO is an EU Specific Targeted Research Project (STREP where new types of biometrics are combined with state-of-the-art unobtrusive technologies in order to enhance security in a wide spectrum of applications. The project aims to develop a modular, robust, multimodal biometrics security authentication and monitoring system, which uses a biodynamic physiological profile, unique for each individual, and advancements of the state of the art in unobtrusive behavioral and other biometrics, such as face, gait recognition, and seat-based anthropometrics. Several shortcomings of existing biometric recognition systems are addressed within this project, which have helped in improving existing sensors, in developing new algorithms, and in designing applications, towards creating new, unobtrusive, biometric authentication procedures in security-sensitive, Ambient Intelligence environments. This paper presents the concept of the ACTIBIO project and describes its unobtrusive authentication demonstrator in a real scenario by focusing on the vision-based biometric recognition modalities.
3D face analysis for demographic biometrics

Energy Technology Data Exchange (ETDEWEB)

Tokola, Ryan A [ORNL; Mikkilineni, Aravind K [ORNL; Boehnen, Chris Bensing [ORNL

2015-01-01

Despite being increasingly easy to acquire, 3D data is rarely used for face-based biometrics applications beyond identification. Recent work in image-based demographic biometrics has enjoyed much success, but these approaches suffer from the well-known limitations of 2D representations, particularly variations in illumination, texture, and pose, as well as a fundamental inability to describe 3D shape. This paper shows that simple 3D shape features in a face-based coordinate system are capable of representing many biometric attributes without problem-specific models or specialized domain knowledge. The same feature vector achieves impressive results for problems as diverse as age estimation, gender classification, and race classification.
Data Acquisition for Modular Biometric Monitoring System

Science.gov (United States)

Chmiel, Alan J. (Inventor); Humphreys, Bradley T. (Inventor); Grodsinsky, Carlos M. (Inventor)

2014-01-01

A modular system for acquiring biometric data includes a plurality of data acquisition modules configured to sample biometric data from at least one respective input channel at a data acquisition rate. A representation of the sampled biometric data is stored in memory of each of the plurality of data acquisition modules. A central control system is in communication with each of the plurality of data acquisition modules through a bus. The central control system is configured to collect data asynchronously, via the bus, from the memory of the plurality of data acquisition modules according to a relative fullness of the memory of the plurality of data acquisition modules.
Heart Electrical Actions as Biometric Indicia

Science.gov (United States)

Schipper, John F. (Inventor); Dusan, Sorin V. (Inventor); Jorgensen, Charles C. (Inventor); Belousof, Eugene (Inventor)

2013-01-01

A method and associated system for use of statistical parameters based on peak amplitudes and/or time interval lengths and/or depolarization-repolarization vector angles and/or depolarization-repolarization vector lengths for PQRST electrical signals associated with heart waves, to identify a person. The statistical parameters, estimated to be at least 192, serve as biometric indicia, to authenticate, or to decline to authenticate, an asserted identity of a candidate person.
A Review of Subsequence Time Series Clustering

Directory of Open Access Journals (Sweden)

Seyedjamal Zolhavarieh

2014-01-01

Full Text Available Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies.
A review of subsequence time series clustering.

Science.gov (United States)

Zolhavarieh, Seyedjamal; Aghabozorgi, Saeed; Teh, Ying Wah

2014-01-01

Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies.
A Review of Subsequence Time Series Clustering

Science.gov (United States)

Teh, Ying Wah

2014-01-01

Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies. PMID:25140332
Biometric Security: Alternatif Pengendalian Dalam Sistem Informasi Akuntansi Terkomputerisasi

OpenAIRE

Tarigan, Josua

2004-01-01

As organization search more secure authentication method for user access, biometric security technology is gaining more and more attention. The implementation of biometric security technology in accounting information systems was physical access, virtual access, e-commerce applications and covert suveillance. There are three phase when an organization implementation biometric technology: strategic planning and budgeting, developing a system reliability plan and documentation. The challenges w...
BIOMETRIC SECURITY: ALTERNATIF PENGENDALIAN DALAM SISTEM INFORMASI AKUNTANSI TERKOMPUTERISASI

OpenAIRE

Josua Tarigan

2004-01-01

As organization search more secure authentication method for user access, biometric security technology is gaining more and more attention. The implementation of biometric security technology in accounting information systems was physical access, virtual access, e-commerce applications and covert suveillance. There are three phase when an organization implementation biometric technology: strategic planning and budgeting, developing a system reliability plan and documentation. The challenges w...
Analysis of Heavy-Tailed Time Series

DEFF Research Database (Denmark)

Xie, Xiaolei

This thesis is about analysis of heavy-tailed time series. We discuss tail properties of real-world equity return series and investigate the possibility that a single tail index is shared by all return series of actively traded equities in a market. Conditions for this hypothesis to be true...... are identified. We study the eigenvalues and eigenvectors of sample covariance and sample auto-covariance matrices of multivariate heavy-tailed time series, and particularly for time series with very high dimensions. Asymptotic approximations of the eigenvalues and eigenvectors of such matrices are found...... and expressed in terms of the parameters of the dependence structure, among others. Furthermore, we study an importance sampling method for estimating rare-event probabilities of multivariate heavy-tailed time series generated by matrix recursion. We show that the proposed algorithm is efficient in the sense...
Adaptive time-variant models for fuzzy-time-series forecasting.

Science.gov (United States)

Wong, Wai-Keung; Bai, Enjian; Chu, Alice Wai-Ching

2010-12-01

A fuzzy time series has been applied to the prediction of enrollment, temperature, stock indices, and other domains. Related studies mainly focus on three factors, namely, the partition of discourse, the content of forecasting rules, and the methods of defuzzification, all of which greatly influence the prediction accuracy of forecasting models. These studies use fixed analysis window sizes for forecasting. In this paper, an adaptive time-variant fuzzy-time-series forecasting model (ATVF) is proposed to improve forecasting accuracy. The proposed model automatically adapts the analysis window size of fuzzy time series based on the prediction accuracy in the training phase and uses heuristic rules to generate forecasting values in the testing phase. The performance of the ATVF model is tested using both simulated and actual time series including the enrollments at the University of Alabama, Tuscaloosa, and the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX). The experiment results show that the proposed ATVF model achieves a significant improvement in forecasting accuracy as compared to other fuzzy-time-series forecasting models.
Biometric estimation of chest wall thickness of female radiation workers as an aid in in-vivo detection of the actinides

International Nuclear Information System (INIS)

Lane, B.H.; Berger, C.D.

1983-01-01

An equation was derived to estimate female chest wall thickness from a series of biometric measurements. This technique will result in improved performance for actinide detection in females by accounting for variations in chest wall thickness in derivation of calibration factors
Time Series Analysis and Forecasting by Example

CERN Document Server

Bisgaard, Soren

2011-01-01

An intuition-based approach enables you to master time series analysis with ease Time Series Analysis and Forecasting by Example provides the fundamental techniques in time series analysis using various examples. By introducing necessary theory through examples that showcase the discussed topics, the authors successfully help readers develop an intuitive understanding of seemingly complicated time series models and their implications. The book presents methodologies for time series analysis in a simplified, example-based approach. Using graphics, the authors discuss each presented example in
Time series with tailored nonlinearities

Science.gov (United States)

Räth, C.; Laut, I.

2015-10-01

It is demonstrated how to generate time series with tailored nonlinearities by inducing well-defined constraints on the Fourier phases. Correlations between the phase information of adjacent phases and (static and dynamic) measures of nonlinearities are established and their origin is explained. By applying a set of simple constraints on the phases of an originally linear and uncorrelated Gaussian time series, the observed scaling behavior of the intensity distribution of empirical time series can be reproduced. The power law character of the intensity distributions being typical for, e.g., turbulence and financial data can thus be explained in terms of phase correlations.
Feature Selection for Nonstationary Data: Application to Human Recognition Using Medical Biometrics.

Science.gov (United States)

Komeili, Majid; Louis, Wael; Armanfard, Narges; Hatzinakos, Dimitrios

2018-05-01

Electrocardiogram (ECG) and transient evoked otoacoustic emission (TEOAE) are among the physiological signals that have attracted significant interest in biometric community due to their inherent robustness to replay and falsification attacks. However, they are time-dependent signals and this makes them hard to deal with in across-session human recognition scenario where only one session is available for enrollment. This paper presents a novel feature selection method to address this issue. It is based on an auxiliary dataset with multiple sessions where it selects a subset of features that are more persistent across different sessions. It uses local information in terms of sample margins while enforcing an across-session measure. This makes it a perfect fit for aforementioned biometric recognition problem. Comprehensive experiments on ECG and TEOAE variability due to time lapse and body posture are done. Performance of the proposed method is compared against seven state-of-the-art feature selection algorithms as well as another six approaches in the area of ECG and TEOAE biometric recognition. Experimental results demonstrate that the proposed method performs noticeably better than other algorithms.
Joint sparse representation for robust multimodal biometrics recognition.

Science.gov (United States)

Shekhar, Sumit; Patel, Vishal M; Nasrabadi, Nasser M; Chellappa, Rama

2014-01-01

Traditional biometric recognition systems rely on a single biometric signature for authentication. While the advantage of using multiple sources of information for establishing the identity has been widely recognized, computational models for multimodal biometrics recognition have only recently received attention. We propose a multimodal sparse representation method, which represents the test data by a sparse linear combination of training data, while constraining the observations from different modalities of the test subject to share their sparse representations. Thus, we simultaneously take into account correlations as well as coupling information among biometric modalities. A multimodal quality measure is also proposed to weigh each modality as it gets fused. Furthermore, we also kernelize the algorithm to handle nonlinearity in data. The optimization problem is solved using an efficient alternative direction method. Various experiments show that the proposed method compares favorably with competing fusion-based methods.

Biometric identification based on feature fusion with PCA and SVM

Science.gov (United States)

Lefkovits, László; Lefkovits, Szidónia; Emerich, Simina

2018-04-01

Biometric identification is gaining ground compared to traditional identification methods. Many biometric measurements may be used for secure human identification. The most reliable among them is the iris pattern because of its uniqueness, stability, unforgeability and inalterability over time. The approach presented in this paper is a fusion of different feature descriptor methods such as HOG, LIOP, LBP, used for extracting iris texture information. The classifiers obtained through the SVM and PCA methods demonstrate the effectiveness of our system applied to one and both irises. The performances measured are highly accurate and foreshadow a fusion system with a rate of identification approaching 100% on the UPOL database.
A definitional framework for the human/biometric sensor interaction model

Science.gov (United States)

Elliott, Stephen J.; Kukula, Eric P.

2010-04-01

Existing definitions for biometric testing and evaluation do not fully explain errors in a biometric system. This paper provides a definitional framework for the Human Biometric-Sensor Interaction (HBSI) model. This paper proposes six new definitions based around two classifications of presentations, erroneous and correct. The new terms are: defective interaction (DI), concealed interaction (CI), false interaction (FI), failure to detect (FTD), failure to extract (FTX), and successfully acquired samples (SAS). As with all definitions, the new terms require a modification to the general biometric model developed by Mansfield and Wayman [1].
Clustering of financial time series

Science.gov (United States)

D'Urso, Pierpaolo; Cappelli, Carmela; Di Lallo, Dario; Massari, Riccardo

2013-05-01

This paper addresses the topic of classifying financial time series in a fuzzy framework proposing two fuzzy clustering models both based on GARCH models. In general clustering of financial time series, due to their peculiar features, needs the definition of suitable distance measures. At this aim, the first fuzzy clustering model exploits the autoregressive representation of GARCH models and employs, in the framework of a partitioning around medoids algorithm, the classical autoregressive metric. The second fuzzy clustering model, also based on partitioning around medoids algorithm, uses the Caiado distance, a Mahalanobis-like distance, based on estimated GARCH parameters and covariances that takes into account the information about the volatility structure of time series. In order to illustrate the merits of the proposed fuzzy approaches an application to the problem of classifying 29 time series of Euro exchange rates against international currencies is presented and discussed, also comparing the fuzzy models with their crisp version.
Trace Attack against Biometric Mobile Applications

Directory of Open Access Journals (Sweden)

Sanaa Ghouzali

2016-01-01

Full Text Available With the exponential increase in the dependence on mobile devices in everyday life, there is a growing concern related to privacy and security issues in the Gulf countries; therefore, it is imperative that security threats should be analyzed in detail. Mobile devices store enormous amounts of personal and financial information, unfortunately without any security. In order to secure mobile devices against different threats, biometrics has been applied and shown to be effective. However, biometric mobile applications are also vulnerable to several types of attacks that can decrease their security. Biometric information itself is considered sensitive data; for example, fingerprints can leave traces in touched objects and facial images can be captured everywhere or accessed by the attacker if the facial image is stored in the mobile device (lost or stolen. Hence, an attacker can easily forge the identity of a legitimate user and access data on a device. In this paper, the effects of a trace attack on the sensitivity of biometric mobile applications are investigated in terms of security and user privacy. Experimental results carried out on facial and fingerprint mobile authentication applications using different databases have shown that these mobile applications are vulnerable to the proposed attack, which poses a serious threat to the overall system security and user privacy.
Analyzing personalized policies for online biometric verification.

Science.gov (United States)

Sadhwani, Apaar; Yang, Yan; Wein, Lawrence M

2014-01-01

Motivated by India's nationwide biometric program for social inclusion, we analyze verification (i.e., one-to-one matching) in the case where we possess similarity scores for 10 fingerprints and two irises between a resident's biometric images at enrollment and his biometric images during his first verification. At subsequent verifications, we allow individualized strategies based on these 12 scores: we acquire a subset of the 12 images, get new scores for this subset that quantify the similarity to the corresponding enrollment images, and use the likelihood ratio (i.e., the likelihood of observing these scores if the resident is genuine divided by the corresponding likelihood if the resident is an imposter) to decide whether a resident is genuine or an imposter. We also consider two-stage policies, where additional images are acquired in a second stage if the first-stage results are inconclusive. Using performance data from India's program, we develop a new probabilistic model for the joint distribution of the 12 similarity scores and find near-optimal individualized strategies that minimize the false reject rate (FRR) subject to constraints on the false accept rate (FAR) and mean verification delay for each resident. Our individualized policies achieve the same FRR as a policy that acquires (and optimally fuses) 12 biometrics for each resident, which represents a five (four, respectively) log reduction in FRR relative to fingerprint (iris, respectively) policies previously proposed for India's biometric program. The mean delay is [Formula: see text] sec for our proposed policy, compared to 30 sec for a policy that acquires one fingerprint and 107 sec for a policy that acquires all 12 biometrics. This policy acquires iris scans from 32-41% of residents (depending on the FAR) and acquires an average of 1.3 fingerprints per resident.
Anti-deception: reliable EEG-based biometrics with real-time capability from the neural response of face rapid serial visual presentation.

Science.gov (United States)

Wu, Qunjian; Yan, Bin; Zeng, Ying; Zhang, Chi; Tong, Li

2018-05-03

The electroencephalogram (EEG) signal represents a subject's specific brain activity patterns and is considered as an ideal biometric given its superior invisibility, non-clonality, and non-coercion. In order to enhance its applicability in identity authentication, a novel EEG-based identity authentication method is proposed based on self- or non-self-face rapid serial visual presentation. In contrast to previous studies that extracted EEG features from rest state or motor imagery, the designed paradigm could obtain a distinct and stable biometric trait with a lower time cost. Channel selection was applied to select specific channels for each user to enhance system portability and improve discriminability between users and imposters. Two different imposter scenarios were designed to test system security, which demonstrate the capability of anti-deception. Fifteen users and thirty imposters participated in the experiment. The mean authentication accuracy values for the two scenarios were 91.31 and 91.61%, with 6 s time cost, which illustrated the precision and real-time capability of the system. Furthermore, in order to estimate the repeatability and stability of our paradigm, another data acquisition session is conducted for each user. Using the classification models generated from the previous sessions, a mean false rejected rate of 7.27% has been achieved, which demonstrates the robustness of our paradigm. Experimental results reveal that the proposed paradigm and methods are effective for EEG-based identity authentication.
Enhancing Privacy for Biometric Identification Cards

Directory of Open Access Journals (Sweden)

2009-01-01

Full Text Available Most developed countries have started the implementation of biometric electronic identification cards, especially passports. The European Union and the United States of America struggle to introduce and standardize these electronic documents. Due to the personal nature of the biometric elements used for the generation of these cards, privacy issues were raised on both sides of the Atlantic Ocean, leading to civilian protests and concerns. The lack of transparency from the public authorities responsible with the implementation of such identification systems, and the poor technological approaches chosen by these authorities, are the main reasons for the negative popularity of the new identification methods. The following article shows an approach that provides all the benefits of modern technological advances in the fields of biometrics and cryptography, without sacrificing the privacy of those that will be the beneficiaries of the new system
Multi-biometric Liveness Detection – A New Perspective

African Journals Online (AJOL)

2016-12-01

Dec 1, 2016 ... Basic Multi-biometric Authentication System was thought to have sealed the vulnerabilities ..... action of a real physical human being and not from a pattern ... of authentication is referred to as multi-biometric fusion, and such a ...
A user authentication scheme using physiological and behavioral biometrics for multitouch devices.

Science.gov (United States)

Koong, Chorng-Shiuh; Yang, Tzu-I; Tseng, Chien-Chao

2014-01-01

With the rapid growth of mobile network, tablets and smart phones have become sorts of keys to access personal secured services in our daily life. People use these devices to manage personal finances, shop on the Internet, and even pay at vending machines. Besides, it also helps us get connected with friends and business partners through social network applications, which were widely used as personal identifications in both real and virtual societies. However, these devices use inherently weak authentication mechanism, based upon passwords and PINs that is not changed all the time. Although forcing users to change password periodically can enhance the security level, it may also be considered annoyances for users. Biometric technologies are straightforward because of the simple authentication process. However, most of the traditional biometrics methodologies require diverse equipment to acquire biometric information, which may be expensive and not portable. This paper proposes a multibiometric user authentication scheme with both physiological and behavioral biometrics. Only simple rotations with fingers on multitouch devices are required to enhance the security level without annoyances for users. In addition, the user credential is replaceable to prevent from the privacy leakage.
A User Authentication Scheme Using Physiological and Behavioral Biometrics for Multitouch Devices

Science.gov (United States)

Koong, Chorng-Shiuh; Tseng, Chien-Chao

2014-01-01

With the rapid growth of mobile network, tablets and smart phones have become sorts of keys to access personal secured services in our daily life. People use these devices to manage personal finances, shop on the Internet, and even pay at vending machines. Besides, it also helps us get connected with friends and business partners through social network applications, which were widely used as personal identifications in both real and virtual societies. However, these devices use inherently weak authentication mechanism, based upon passwords and PINs that is not changed all the time. Although forcing users to change password periodically can enhance the security level, it may also be considered annoyances for users. Biometric technologies are straightforward because of the simple authentication process. However, most of the traditional biometrics methodologies require diverse equipment to acquire biometric information, which may be expensive and not portable. This paper proposes a multibiometric user authentication scheme with both physiological and behavioral biometrics. Only simple rotations with fingers on multitouch devices are required to enhance the security level without annoyances for users. In addition, the user credential is replaceable to prevent from the privacy leakage. PMID:25147864
A User Authentication Scheme Using Physiological and Behavioral Biometrics for Multitouch Devices

Directory of Open Access Journals (Sweden)

Chorng-Shiuh Koong

2014-01-01

Full Text Available With the rapid growth of mobile network, tablets and smart phones have become sorts of keys to access personal secured services in our daily life. People use these devices to manage personal finances, shop on the Internet, and even pay at vending machines. Besides, it also helps us get connected with friends and business partners through social network applications, which were widely used as personal identifications in both real and virtual societies. However, these devices use inherently weak authentication mechanism, based upon passwords and PINs that is not changed all the time. Although forcing users to change password periodically can enhance the security level, it may also be considered annoyances for users. Biometric technologies are straightforward because of the simple authentication process. However, most of the traditional biometrics methodologies require diverse equipment to acquire biometric information, which may be expensive and not portable. This paper proposes a multibiometric user authentication scheme with both physiological and behavioral biometrics. Only simple rotations with fingers on multitouch devices are required to enhance the security level without annoyances for users. In addition, the user credential is replaceable to prevent from the privacy leakage.
Biometric Collection, Transmission and Storage Standards. Version 1.1

National Research Council Canada - National Science Library

2006-01-01

This document provides a comprehensive technical reference that lists published biometric standards and describes their applicability to the biometric functions described in the Capstone Concept of Operations (CONOPS...
Biometric Attendance and Big Data Analysis for Optimizing Work Processes.

Science.gov (United States)

Verma, Neetu; Xavier, Teenu; Agrawal, Deepak

2016-01-01

Although biometric attendance management is available, large healthcare organizations have difficulty in big data analysis for optimization of work processes. The aim of this project was to assess the implementation of a biometric attendance system and its utility following big data analysis. In this prospective study the implementation of biometric system was evaluated over 3 month period at our institution. Software integration with other existing systems for data analysis was also evaluated. Implementation of the biometric system could be successfully done over a two month period with enrollment of 10,000 employees into the system. However generating reports and taking action this large number of staff was a challenge. For this purpose software was made for capturing the duty roster of each employee and integrating it with the biometric system and adding an SMS gateway. This helped in automating the process of sending SMSs to each employee who had not signed in. Standalone biometric systems have limited functionality in large organizations unless it is meshed with employee duty roster.
User-Centric Key Entropy: Study of Biometric Key Derivation Subject to Spoofing Attacks

Directory of Open Access Journals (Sweden)

Lavinia Mihaela Dinca

2017-02-01

Full Text Available Biometric data can be used as input for PKI key pair generation. The concept of not saving the private key is very appealing, but the implementation of such a system shouldn’t be rushed because it might prove less secure then current PKI infrastructure. One biometric characteristic can be easily spoofed, so it was believed that multi-modal biometrics would offer more security, because spoofing two or more biometrics would be very hard. This notion, of increased security of multi-modal biometric systems, was disproved for authentication and matching, studies showing that not only multi-modal biometric systems are not more secure, but they introduce additional vulnerabilities. This paper is a study on the implications of spoofing biometric data for retrieving the derived key. We demonstrate that spoofed biometrics can yield the same key, which in turn will lead an attacker to obtain the private key. A practical implementation is proposed using fingerprint and iris as biometrics and the fuzzy extractor for biometric key extraction. Our experiments show what happens when the biometric data is spoofed for both uni-modal systems and multi-modal. In case of multi-modal system tests were performed when spoofing one biometric or both. We provide detailed analysis of every scenario in regard to successful tests and overall key entropy. Our paper defines a biometric PKI scenario and an in depth security analysis for it. The analysis can be viewed as a blueprint for implementations of future similar systems, because it highlights the main security vulnerabilities for bioPKI. The analysis is not constrained to the biometric part of the system, but covers CA security, sensor security, communication interception, RSA encryption vulnerabilities regarding key entropy, and much more.
Biometrics Foundation Documents

Science.gov (United States)

2009-01-01

adjudication ( legal ) process. Forensics usually requires days of processing (versus seconds for biometrics) and are held to much higher accuracy...Living Body,” Medicina Philosophica, 11:620-629, 1992. 2 K. Shimizu and K. Yamomoto,“Imaging of Physiological Functions By Laser Transillumination
Data Mining Smart Energy Time Series

Directory of Open Access Journals (Sweden)

Janina POPEANGA

2015-07-01

Full Text Available With the advent of smart metering technology the amount of energy data will increase significantly and utilities industry will have to face another big challenge - to find relationships within time-series data and even more - to analyze such huge numbers of time series to find useful patterns and trends with fast or even real-time response. This study makes a small review of the literature in the field, trying to demonstrate how essential is the application of data mining techniques in the time series to make the best use of this large quantity of data, despite all the difficulties. Also, the most important Time Series Data Mining techniques are presented, highlighting their applicability in the energy domain.
The ocular biometric differences of diabetic patients.

Science.gov (United States)

Kocatürk, Tolga; Zengin, Mehmet Özgür; Cakmak, Harun; Evliçoglu, Gökhan Evren; Dündar, Sema Oruç; Omürlü, Imran Kurt; Unübol, Mustafa; Güney, Engin

2014-01-01

To investigate the differences in ocular biometric and keratometric characteristics in comparison with biometric measurements using the noncontact optical low coherence reflectometer (OLCR) (Lenstar LS 900, Haag-Streit) on diabetic patients. The eyes of 170 patients were included in this study, including 81 diabetic and 89 nondiabetic subjects. Optical biometric measurements of diabetic and nondiabetic patients (between the ages of 25 and 85 years) who applied to the ophthalmology clinic were noted from March to June 2013. Detailed ophthalmologic examinations were done for every subject. Biometric measurements were done using the noncontact OLCR device. Patient age ranged from 29 to 83 years. Subgroup analyses were done in diabetic patients according to their Hba1C levels. The minimum Hba1C value was 5.3, maximum was 12.4, and mean was 7.56 ± 1.48. The median duration of diabetes was 5 years (25th-75th percentile 3.00-11.75). Diabetic patients were found to have thicker lens and shallower anterior chamber in both eyes compared to nondiabetic control subjects. There were no statistical differences between the groups according to central corneal thickness, axial length, or keratometric values in both eyes. However, lens thicknesses were found to be thicker and anterior chamber depth values were found to be shallower in the diabetic group in both eyes. It may useful to determine eyeglasses prescription, refractive surgery calculation, lens selection, and previous cataract surgery according to biometric measurements after the regulation of blood glucose.
Predicting chaotic time series

International Nuclear Information System (INIS)

Farmer, J.D.; Sidorowich, J.J.

1987-01-01

We present a forecasting technique for chaotic data. After embedding a time series in a state space using delay coordinates, we ''learn'' the induced nonlinear mapping using local approximation. This allows us to make short-term predictions of the future behavior of a time series, using information based only on past values. We present an error estimate for this technique, and demonstrate its effectiveness by applying it to several examples, including data from the Mackey-Glass delay differential equation, Rayleigh-Benard convection, and Taylor-Couette flow
New comparative clinical and biometric findings between acute primary angle-closure and glaucomatous eyes with narrow angle

Directory of Open Access Journals (Sweden)

Rafael Vidal Mérula

2010-12-01

Full Text Available Purpose: To compare, clinically and biometrically, affected and fellow acute primary angle-closure (APAC eyes and glaucomatous eyes with narrow angle (NA. Methods: Comparative case series; 30 patients with APAC and 27 glaucomatous patients with NA were evaluated. Keratometry (K, central corneal thickness (CCT, lens thickness (LT, axial length (AL and anterior chamber depth (ACD were measured. Parameters defined as lens posisiton (LP and relative lens position (RLP were calculated. Results: Biometric difference between APAC-affected and fellow eyes was found only in LP (P=0.046. When fellow eyes were compared to glaucomatous eyes with NA, differences were found in ACD (P=0.009, AL (P=0.010, and LT/AL (P=0.005. The comparison between APAC-affected and glaucomatous eyes with NA showed significant differences in almost all biometric parameters, except for LT (P=0.148 and RLP (P=0.374. We found that the logistic regression model (LRM, built with three parameters (K, CCT and LT/AL, higher than 0.334 could be a reasonable instrument to differentiate APAC eyes from glaucomatous eyes with NA. Conclusions: This study showed that APAC-affected and fellow eyes have similar biometric features, and glaucomatous eyes with NA have a less crowded anterior segment. The LRM built showed promising results in distinguishing APAC from glaucomatous eyes with NA.
Heartbeat Signal from Facial Video for Biometric Recognition

DEFF Research Database (Denmark)

Haque, Mohammad Ahsanul; Nasrollahi, Kamal; Moeslund, Thomas B.

2015-01-01

Different biometric traits such as face appearance and heartbeat signal from Electrocardiogram (ECG)/Phonocardiogram (PCG) are widely used in the human identity recognition. Recent advances in facial video based measurement of cardio-physiological parameters such as heartbeat rate, respiratory rate......, and blood volume pressure provide the possibility of extracting heartbeat signal from facial video instead of using obtrusive ECG or PCG sensors in the body. This paper proposes the Heartbeat Signal from Facial Video (HSFV) as a new biometric trait for human identity recognition, for the first time...... to the best of our knowledge. Feature extraction from the HSFV is accomplished by employing Radon transform on a waterfall model of the replicated HSFV. The pairwise Minkowski distances are obtained from the Radon image as the features. The authentication is accomplished by a decision tree based supervised...

Measuring multiscaling in financial time-series

International Nuclear Information System (INIS)

Buonocore, R.J.; Aste, T.; Di Matteo, T.

2016-01-01

We discuss the origin of multiscaling in financial time-series and investigate how to best quantify it. Our methodology consists in separating the different sources of measured multifractality by analyzing the multi/uni-scaling behavior of synthetic time-series with known properties. We use the results from the synthetic time-series to interpret the measure of multifractality of real log-returns time-series. The main finding is that the aggregation horizon of the returns can introduce a strong bias effect on the measure of multifractality. This effect can become especially important when returns distributions have power law tails with exponents in the range (2, 5). We discuss the right aggregation horizon to mitigate this bias.
Semiparametric copula models for biometric score level fusion

NARCIS (Netherlands)

Susyanto, N.

2016-01-01

In biometric recognition, biometric samples (images of faces, fingerprints, voices, gaits, etc.) of people are compared and matchers (classifiers) indicate the level of similarity between any pair of samples by a score. If we model the joint distribution of all scores by a (semiparametric) Gaussian
Time averaging, ageing and delay analysis of financial time series

Science.gov (United States)

Cherstvy, Andrey G.; Vinod, Deepak; Aghion, Erez; Chechkin, Aleksei V.; Metzler, Ralf

2017-06-01

We introduce three strategies for the analysis of financial time series based on time averaged observables. These comprise the time averaged mean squared displacement (MSD) as well as the ageing and delay time methods for varying fractions of the financial time series. We explore these concepts via statistical analysis of historic time series for several Dow Jones Industrial indices for the period from the 1960s to 2015. Remarkably, we discover a simple universal law for the delay time averaged MSD. The observed features of the financial time series dynamics agree well with our analytical results for the time averaged measurables for geometric Brownian motion, underlying the famed Black-Scholes-Merton model. The concepts we promote here are shown to be useful for financial data analysis and enable one to unveil new universal features of stock market dynamics.
Unveiling the Biometric Potential of Finger-Based ECG Signals

Science.gov (United States)

Lourenço, André; Silva, Hugo; Fred, Ana

2011-01-01

The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications. PMID:21837235
Unveiling the biometric potential of finger-based ECG signals.

Science.gov (United States)

Lourenço, André; Silva, Hugo; Fred, Ana

2011-01-01

The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications.
Applied time series analysis

CERN Document Server

Woodward, Wayne A; Elliott, Alan C

2011-01-01

""There is scarcely a standard technique that the reader will find left out … this book is highly recommended for those requiring a ready introduction to applicable methods in time series and serves as a useful resource for pedagogical purposes.""-International Statistical Review (2014), 82""Current time series theory for practice is well summarized in this book.""-Emmanuel Parzen, Texas A&M University""What an extraordinary range of topics covered, all very insightfully. I like [the authors'] innovations very much, such as the AR factor table.""-David Findley, U.S. Census Bureau (retired)""…
Comparison of DCT, SVD and BFOA based multimodal biometric watermarking system

Directory of Open Access Journals (Sweden)

S. Anu H. Nair

2015-12-01

Full Text Available Digital image watermarking is a major domain for hiding the biometric information, in which the watermark data are made to be concealed inside a host image imposing imperceptible change in the picture. Due to the advance in digital image watermarking, the majority of research aims to make a reliable improvement in robustness to prevent the attack. The reversible invisible watermarking scheme is used for fingerprint and iris multimodal biometric system. A novel approach is used for fusing different biometric modalities. Individual unique modalities of fingerprint and iris biometric are extracted and fused using different fusion techniques. The performance of different fusion techniques is evaluated and the Discrete Wavelet Transform fusion method is identified as the best. Then the best fused biometric template is watermarked into a cover image. The various watermarking techniques such as the Discrete Cosine Transform (DCT, Singular Value Decomposition (SVD and Bacterial Foraging Optimization Algorithm (BFOA are implemented to the fused biometric feature image. Performance of watermarking systems is compared using different metrics. It is found that the watermarked images are found robust over different attacks and they are able to reverse the biometric template for Bacterial Foraging Optimization Algorithm (BFOA watermarking technique.
Behavioral and physical biometric characteristics modeling used for ITS security improvement

Directory of Open Access Journals (Sweden)

Miroslav BAČA

2009-01-01

Full Text Available Biometric technologies rely on specific biometric characteristics that are used for recognition. The particular characteristic for a given situation can be described through a serious of descriptive parameters including ease of collecting, permanence, measurably, acceptability, deceptiveness, universality, uniqueness, sample cost, system cost, database size, as well as environmental factors. By using our ontology-based framework for adequacy of biometric systems, we introduce a model for using biometric technologies in ITS. Such technologies increase security, safety and protection of ITS.
21 CFR 1311.116 - Additional requirements for biometrics.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 9 2010-04-01 2010-04-01 false Additional requirements for biometrics. 1311.116 Section 1311.116 Food and Drugs DRUG ENFORCEMENT ADMINISTRATION, DEPARTMENT OF JUSTICE REQUIREMENTS FOR... for biometrics. (a) If one of the factors used to authenticate to the electronic prescription...
Security analysis for biometric data in ID documents

NARCIS (Netherlands)

Schimke, S.; Kiltz, S.; Vielhauer, C.; Kalker, A.A.C.M.

2005-01-01

In this paper we analyze chances and challenges with respect to the security of using biometrics in ID documents. We identify goals for ID documents, set by national and international authorities, and discuss the degree of security, which is obtainable with the inclusion of biometric into documents
Towards non-repudiable authentication through biometrics and smart cards

CSIR Research Space (South Africa)

Msiza, I

2012-10-01

Full Text Available ? biometrics and smart cards Part B: Biometrics ? CSIR 2012 Slide 7 Biometric Authentication ? CSIR 2012 Slide 8 ? A science that uses a person?s behavioral and/or physiological traits to establish their identify, or verify their claimed identity.../or characteristics of some thing ? This thing can be anything, however in the context of this discussion, this thing could be a person, a network device, or even an identity authentication device itself ? This act or process of verifying these attributes could...
Entropic Analysis of Electromyography Time Series

Science.gov (United States)

Kaufman, Miron; Sung, Paul

2005-03-01

We are in the process of assessing the effectiveness of fractal and entropic measures for the diagnostic of low back pain from surface electromyography (EMG) time series. Surface electromyography (EMG) is used to assess patients with low back pain. In a typical EMG measurement, the voltage is measured every millisecond. We observed back muscle fatiguing during one minute, which results in a time series with 60,000 entries. We characterize the complexity of time series by computing the Shannon entropy time dependence. The analysis of the time series from different relevant muscles from healthy and low back pain (LBP) individuals provides evidence that the level of variability of back muscle activities is much larger for healthy individuals than for individuals with LBP. In general the time dependence of the entropy shows a crossover from a diffusive regime to a regime characterized by long time correlations (self organization) at about 0.01s.
Spectroscopically Enhanced Method and System for Multi-Factor Biometric Authentication

Science.gov (United States)

Pishva, Davar

This paper proposes a spectroscopic method and system for preventing spoofing of biometric authentication. One of its focus is to enhance biometrics authentication with a spectroscopic method in a multifactor manner such that a person's unique ‘spectral signatures’ or ‘spectral factors’ are recorded and compared in addition to a non-spectroscopic biometric signature to reduce the likelihood of imposter getting authenticated. By using the ‘spectral factors’ extracted from reflectance spectra of real fingers and employing cluster analysis, it shows how the authentic fingerprint image presented by a real finger can be distinguished from an authentic fingerprint image embossed on an artificial finger, or molded on a fingertip cover worn by an imposter. This paper also shows how to augment two widely used biometrics systems (fingerprint and iris recognition devices) with spectral biometrics capabilities in a practical manner and without creating much overhead or inconveniencing their users.
DTIC Review: Biometric Security

National Research Council Canada - National Science Library

2007-01-01

...: Biometrics, the study of methods for uniquely recognizing humans based upon one or more intrinsic physical or behavioral traits, is a critical tool used in law enforcement, computer security and homeland defense...
A Cross-Layer Biometric Recognition System for Mobile IoT Devices

Directory of Open Access Journals (Sweden)

Shayan Taheri

2018-02-01

Full Text Available A biometric recognition system is one of the leading candidates for the current and the next generation of smart visual systems. The visual system is the engine of the surveillance cameras that have great importance for intelligence and security purposes. These surveillance devices can be a target of adversaries for accomplishing various malicious scenarios such as disabling the camera in critical times or the lack of recognition of a criminal. In this work, we propose a cross-layer biometric recognition system that has small computational complexity and is suitable for mobile Internet of Things (IoT devices. Furthermore, due to the involvement of both hardware and software in realizing this system in a decussate and chaining structure, it is easier to locate and provide alternative paths for the system flow in the case of an attack. For security analysis of this system, one of the elements of this system named the advanced encryption standard (AES is infected by four different Hardware Trojansthat target different parts of this module. The purpose of these Trojans is to sabotage the biometric data that are under process by the biometric recognition system. All of the software and the hardware modules of this system are implemented using MATLAB and Verilog HDL, respectively. According to the performance evaluation results, the system shows an acceptable performance in recognizing healthy biometric data. It is able to detect the infected data, as well. With respect to its hardware results, the system may not contribute significantly to the hardware design parameters of a surveillance camera considering all the hardware elements within the device.
A cancelable biometric scheme based on multi-lead ECGs.

Science.gov (United States)

Peng-Tzu Chen; Shun-Chi Wu; Jui-Hsuan Hsieh

2017-07-01

Biometric technologies offer great advantages over other recognition methods, but there are concerns that they may compromise the privacy of individuals. In this paper, an electrocardiogram (ECG)-based cancelable biometric scheme is proposed to relieve such concerns. In this scheme, distinct biometric templates for a given beat bundle are constructed via "subspace collapsing." To determine the identity of any unknown beat bundle, the multiple signal classification (MUSIC) algorithm, incorporating a "suppression and poll" strategy, is adopted. Unlike the existing cancelable biometric schemes, knowledge of the distortion transform is not required for recognition. Experiments with real ECGs from 285 subjects are presented to illustrate the efficacy of the proposed scheme. The best recognition rate of 97.58 % was achieved under the test condition N train = 10 and N test = 10.
Forensic biometrics: From two communities to one discipline

NARCIS (Netherlands)

Meuwly, Didier; Meuwly, Didier; Veldhuis, Raymond N.J.

2012-01-01

This article describes how the fields of biometrics and forensic science can contribute and benefit from each other. The aim is to foster the development of new methods and tools improving the current forensic biometric applications and allowing for the creation of new ones. The article begins with
Biometrics Technology Review 2002

National Research Council Canada - National Science Library

Blackburn, T

2003-01-01

.... The report characterizes the main categories of biometric techniques, with a focus on face recognition, which is the least intrusive but most effective means of applying filters at access points to the country...
[Biometric identification method for ECG based on the piecewise linear representation (PLR) and dynamic time warping (DTW)].

Science.gov (United States)

Yang, Licai; Shen, Jun; Bao, Shudi; Wei, Shoushui

2013-10-01

To treat the problem of identification performance and the complexity of the algorithm, we proposed a piecewise linear representation and dynamic time warping (PLR-DTW) method for ECG biometric identification. Firstly we detected R peaks to get the heartbeats after denoising preprocessing. Then we used the PLR method to keep important information of an ECG signal segment while reducing the data dimension at the same time. The improved DTW method was used for similarity measurements between the test data and the templates. The performance evaluation was carried out on the two ECG databases: PTB and MIT-BIH. The analystic results showed that compared to the discrete wavelet transform method, the proposed PLR-DTW method achieved a higher accuracy rate which is nearly 8% of rising, and saved about 30% operation time, and this demonstrated that the proposed method could provide a better performance.
Quantifying memory in complex physiological time-series.

Science.gov (United States)

Shirazi, Amir H; Raoufy, Mohammad R; Ebadi, Haleh; De Rui, Michele; Schiff, Sami; Mazloom, Roham; Hajizadeh, Sohrab; Gharibzadeh, Shahriar; Dehpour, Ahmad R; Amodio, Piero; Jafari, G Reza; Montagnese, Sara; Mani, Ali R

2013-01-01

In a time-series, memory is a statistical feature that lasts for a period of time and distinguishes the time-series from a random, or memory-less, process. In the present study, the concept of "memory length" was used to define the time period, or scale over which rare events within a physiological time-series do not appear randomly. The method is based on inverse statistical analysis and provides empiric evidence that rare fluctuations in cardio-respiratory time-series are 'forgotten' quickly in healthy subjects while the memory for such events is significantly prolonged in pathological conditions such as asthma (respiratory time-series) and liver cirrhosis (heart-beat time-series). The memory length was significantly higher in patients with uncontrolled asthma compared to healthy volunteers. Likewise, it was significantly higher in patients with decompensated cirrhosis compared to those with compensated cirrhosis and healthy volunteers. We also observed that the cardio-respiratory system has simple low order dynamics and short memory around its average, and high order dynamics around rare fluctuations.

Optimization of a Biometric System Based on Acoustic Images

Directory of Open Access Journals (Sweden)

Alberto Izquierdo Fuente

2014-01-01

Full Text Available On the basis of an acoustic biometric system that captures 16 acoustic images of a person for 4 frequencies and 4 positions, a study was carried out to improve the performance of the system. On a first stage, an analysis to determine which images provide more information to the system was carried out showing that a set of 12 images allows the system to obtain results that are equivalent to using all of the 16 images. Finally, optimization techniques were used to obtain the set of weights associated with each acoustic image that maximizes the performance of the biometric system. These results improve significantly the performance of the preliminary system, while reducing the time of acquisition and computational burden, since the number of acoustic images was reduced.
Optimization of a Biometric System Based on Acoustic Images

Science.gov (United States)

Izquierdo Fuente, Alberto; Del Val Puente, Lara; Villacorta Calvo, Juan J.; Raboso Mateos, Mariano

2014-01-01

On the basis of an acoustic biometric system that captures 16 acoustic images of a person for 4 frequencies and 4 positions, a study was carried out to improve the performance of the system. On a first stage, an analysis to determine which images provide more information to the system was carried out showing that a set of 12 images allows the system to obtain results that are equivalent to using all of the 16 images. Finally, optimization techniques were used to obtain the set of weights associated with each acoustic image that maximizes the performance of the biometric system. These results improve significantly the performance of the preliminary system, while reducing the time of acquisition and computational burden, since the number of acoustic images was reduced. PMID:24616643
Effective Feature Preprocessing for Time Series Forecasting

DEFF Research Database (Denmark)

Zhao, Junhua; Dong, Zhaoyang; Xu, Zhao

2006-01-01

Time series forecasting is an important area in data mining research. Feature preprocessing techniques have significant influence on forecasting accuracy, therefore are essential in a forecasting model. Although several feature preprocessing techniques have been applied in time series forecasting...... performance in time series forecasting. It is demonstrated in our experiment that, effective feature preprocessing can significantly enhance forecasting accuracy. This research can be a useful guidance for researchers on effectively selecting feature preprocessing techniques and integrating them with time...... series forecasting models....
Real-time Identification System using Mobile Hand-held Devices: Mobile Biometrics Evaluation Framework

Science.gov (United States)

2014-04-01

test server, transmit five test cases over both WIFI and 3G , and receive accurate results. The second Study output, the Mobile Biometrics Evaluation...wired (USB), near field (Bluetooth), wireless (802.11) and cellular ( 2G / 3G ) connectivity. Satellite (BGAN) devices have been deployed, in conjunction...Wireless Connectivity: 802.11b, 802.11g, Bluetooth Cellular Connectivity: GSM [ 2G ], UMTS [ 3G ] Internal RAM (GB): 128 Internal Storage (GB): 128
Animal biometrics: quantifying and detecting phenotypic appearance.

Science.gov (United States)

Kühl, Hjalmar S; Burghardt, Tilo

2013-07-01

Animal biometrics is an emerging field that develops quantified approaches for representing and detecting the phenotypic appearance of species, individuals, behaviors, and morphological traits. It operates at the intersection between pattern recognition, ecology, and information sciences, producing computerized systems for phenotypic measurement and interpretation. Animal biometrics can benefit a wide range of disciplines, including biogeography, population ecology, and behavioral research. Currently, real-world applications are gaining momentum, augmenting the quantity and quality of ecological data collection and processing. However, to advance animal biometrics will require integration of methodologies among the scientific disciplines involved. Such efforts will be worthwhile because the great potential of this approach rests with the formal abstraction of phenomics, to create tractable interfaces between different organizational levels of life. Copyright © 2013 Elsevier Ltd. All rights reserved.
Practical biometrics from aspiration to implementation

CERN Document Server

Ashbourn, Julian

2015-01-01

This practically-focused text presents a hands-on guide to making biometric technology work in real-life scenarios. Extensively revised and updated, this new edition takes a fresh look at what it takes to integrate biometrics into wider applications. An emphasis is placed on the importance of a complete understanding of the broader scenario, covering technical, human and implementation factors. This understanding may then be exercised through interactive chapters dealing with educational software utilities and the BANTAM Program Manager. Topics and features: provides a concise introduction t
Privacy Enhancements for Inexact Biometric Templates

Science.gov (United States)

Ratha, Nalini; Chikkerur, Sharat; Connell, Jonathan; Bolle, Ruud

Traditional authentication schemes utilize tokens or depend on some secret knowledge possessed by the user for verifying his or her identity. Although these techniques are widely used, they have several limitations. Both tokenand knowledge-based approaches cannot differentiate between an authorized user and an impersonator having access to the tokens or passwords. Biometrics-based authentication schemes overcome these limitations while offering usability advantages in the area of password management. However, despite its obvious advantages, the use of biometrics raises several security and privacy concerns.
On the Privacy Protection of Biometric Traits: Palmprint, Face, and Signature

Science.gov (United States)

Panigrahy, Saroj Kumar; Jena, Debasish; Korra, Sathya Babu; Jena, Sanjay Kumar

Biometrics are expected to add a new level of security to applications, as a person attempting access must prove who he or she really is by presenting a biometric to the system. The recent developments in the biometrics area have lead to smaller, faster and cheaper systems, which in turn has increased the number of possible application areas for biometric identity verification. The biometric data, being derived from human bodies (and especially when used to identify or verify those bodies) is considered personally identifiable information (PII). The collection, use and disclosure of biometric data — image or template, invokes rights on the part of an individual and obligations on the part of an organization. As biometric uses and databases grow, so do concerns that the personal data collected will not be used in reasonable and accountable ways. Privacy concerns arise when biometric data are used for secondary purposes, invoking function creep, data matching, aggregation, surveillance and profiling. Biometric data transmitted across networks and stored in various databases by others can also be stolen, copied, or otherwise misused in ways that can materially affect the individual involved. As Biometric systems are vulnerable to replay, database and brute-force attacks, such potential attacks must be analysed before they are massively deployed in security systems. Along with security, also the privacy of the users is an important factor as the constructions of lines in palmprints contain personal characteristics, from face images a person can be recognised, and fake signatures can be practised by carefully watching the signature images available in the database. We propose a cryptographic approach to encrypt the images of palmprints, faces, and signatures by an advanced Hill cipher technique for hiding the information in the images. It also provides security to these images from being attacked by above mentioned attacks. So, during the feature extraction, the
EEG biometric identification: a thorough exploration of the time-frequency domain

Science.gov (United States)

DelPozo-Banos, Marcos; Travieso, Carlos M.; Weidemann, Christoph T.; Alonso, Jesús B.

2015-10-01

Objective. Although interest in using electroencephalogram (EEG) activity for subject identification has grown in recent years, the state of the art still lacks a comprehensive exploration of the discriminant information within it. This work aims to fill this gap, and in particular, it focuses on the time-frequency representation of the EEG. Approach. We executed qualitative and quantitative analyses of six publicly available data sets following a sequential experimentation approach. This approach was divided in three blocks analysing the configuration of the power spectrum density, the representation of the data and the properties of the discriminant information. A total of ten experiments were applied. Main results. Results show that EEG information below 40 Hz is unique enough to discriminate across subjects (a maximum of 100 subjects were evaluated here), regardless of the recorded cognitive task or the sensor location. Moreover, the discriminative power of rhythms follows a W-like shape between 1 and 40 Hz, with the central peak located at the posterior rhythm (around 10 Hz). This information is maximized with segments of around 2 s, and it proved to be moderately constant across montages and time. Significance. Therefore, we characterize how EEG activity differs across individuals and detail the optimal conditions to detect subject-specific information. This work helps to clarify the results of previous studies and to solve some unanswered questions. Ultimately, it will serve as guide for the design of future biometric systems.
Chaotic secure content-based hidden transmission of biometric templates

International Nuclear Information System (INIS)

Khan, Muhammad Khurram; Zhang Jiashu; Tian Lei

2007-01-01

The large-scale proliferation of biometric verification systems creates a demand for effective and reliable security and privacy of its data. Like passwords and PIN codes, biometric data is also not secret and if it is compromised, the integrity of the whole verification system could be at high risk. To address these issues, this paper presents a novel chaotic secure content-based hidden transmission scheme of biometric data. Encryption and data hiding techniques are used to improve the security and secrecy of the transmitted templates. Secret keys are generated by the biometric image and used as the parameter value and initial condition of the chaotic map, and each transaction session has different secret keys to protect from the attacks. Two chaotic maps are incorporated for the encryption to resolve the finite word length effect and to improve the system's resistance against attacks. Encryption is applied on the biometric templates before hiding into the cover/host images to make them secure, and then templates are hidden into the cover image. Experimental results show that the security, performance, and accuracy of the presented scheme are encouraging comparable with other methods found in the current literature
Chaotic secure content-based hidden transmission of biometric templates

Energy Technology Data Exchange (ETDEWEB)

Khan, Muhammad Khurram [Research Group for Biometrics and Security, Sichuan Province Key Lab of Signal and Information Processing, Southwest Jiaotong University, Chengdu 610031, Sichuan (China)]. E-mail: khurram.khan@scientist.com; Zhang Jiashu [Research Group for Biometrics and Security, Sichuan Province Key Lab of Signal and Information Processing, Southwest Jiaotong University, Chengdu 610031, Sichuan (China); Tian Lei [Research Group for Biometrics and Security, Sichuan Province Key Lab of Signal and Information Processing, Southwest Jiaotong University, Chengdu 610031, Sichuan (China)

2007-06-15

The large-scale proliferation of biometric verification systems creates a demand for effective and reliable security and privacy of its data. Like passwords and PIN codes, biometric data is also not secret and if it is compromised, the integrity of the whole verification system could be at high risk. To address these issues, this paper presents a novel chaotic secure content-based hidden transmission scheme of biometric data. Encryption and data hiding techniques are used to improve the security and secrecy of the transmitted templates. Secret keys are generated by the biometric image and used as the parameter value and initial condition of the chaotic map, and each transaction session has different secret keys to protect from the attacks. Two chaotic maps are incorporated for the encryption to resolve the finite word length effect and to improve the system's resistance against attacks. Encryption is applied on the biometric templates before hiding into the cover/host images to make them secure, and then templates are hidden into the cover image. Experimental results show that the security, performance, and accuracy of the presented scheme are encouraging comparable with other methods found in the current literature.
Modeling associations between latent event processes governing time series of pulsing hormones.

Science.gov (United States)

Liu, Huayu; Carlson, Nichole E; Grunwald, Gary K; Polotsky, Alex J

2017-10-31

This work is motivated by a desire to quantify relationships between two time series of pulsing hormone concentrations. The locations of pulses are not directly observed and may be considered latent event processes. The latent event processes of pulsing hormones are often associated. It is this joint relationship we model. Current approaches to jointly modeling pulsing hormone data generally assume that a pulse in one hormone is coupled with a pulse in another hormone (one-to-one association). However, pulse coupling is often imperfect. Existing joint models are not flexible enough for imperfect systems. In this article, we develop a more flexible class of pulse association models that incorporate parameters quantifying imperfect pulse associations. We propose a novel use of the Cox process model as a model of how pulse events co-occur in time. We embed the Cox process model into a hormone concentration model. Hormone concentration is the observed data. Spatial birth and death Markov chain Monte Carlo is used for estimation. Simulations show the joint model works well for quantifying both perfect and imperfect associations and offers estimation improvements over single hormone analyses. We apply this model to luteinizing hormone (LH) and follicle stimulating hormone (FSH), two reproductive hormones. Use of our joint model results in an ability to investigate novel hypotheses regarding associations between LH and FSH secretion in obese and non-obese women. © 2017, The International Biometric Society.
Statistical criteria for characterizing irradiance time series.

Energy Technology Data Exchange (ETDEWEB)

Stein, Joshua S.; Ellis, Abraham; Hansen, Clifford W.

2010-10-01

We propose and examine several statistical criteria for characterizing time series of solar irradiance. Time series of irradiance are used in analyses that seek to quantify the performance of photovoltaic (PV) power systems over time. Time series of irradiance are either measured or are simulated using models. Simulations of irradiance are often calibrated to or generated from statistics for observed irradiance and simulations are validated by comparing the simulation output to the observed irradiance. Criteria used in this comparison should derive from the context of the analyses in which the simulated irradiance is to be used. We examine three statistics that characterize time series and their use as criteria for comparing time series. We demonstrate these statistics using observed irradiance data recorded in August 2007 in Las Vegas, Nevada, and in June 2009 in Albuquerque, New Mexico.
Homogenising time series: beliefs, dogmas and facts

Science.gov (United States)

Domonkos, P.

2011-06-01

In the recent decades various homogenisation methods have been developed, but the real effects of their application on time series are still not known sufficiently. The ongoing COST action HOME (COST ES0601) is devoted to reveal the real impacts of homogenisation methods more detailed and with higher confidence than earlier. As a part of the COST activity, a benchmark dataset was built whose characteristics approach well the characteristics of real networks of observed time series. This dataset offers much better opportunity than ever before to test the wide variety of homogenisation methods, and analyse the real effects of selected theoretical recommendations. Empirical results show that real observed time series usually include several inhomogeneities of different sizes. Small inhomogeneities often have similar statistical characteristics than natural changes caused by climatic variability, thus the pure application of the classic theory that change-points of observed time series can be found and corrected one-by-one is impossible. However, after homogenisation the linear trends, seasonal changes and long-term fluctuations of time series are usually much closer to the reality than in raw time series. Some problems around detecting multiple structures of inhomogeneities, as well as that of time series comparisons within homogenisation procedures are discussed briefly in the study.
Ocean time-series near Bermuda: Hydrostation S and the US JGOFS Bermuda Atlantic time-series study

Science.gov (United States)

Michaels, Anthony F.; Knap, Anthony H.

1992-01-01

Bermuda is the site of two ocean time-series programs. At Hydrostation S, the ongoing biweekly profiles of temperature, salinity and oxygen now span 37 years. This is one of the longest open-ocean time-series data sets and provides a view of decadal scale variability in ocean processes. In 1988, the U.S. JGOFS Bermuda Atlantic Time-series Study began a wide range of measurements at a frequency of 14-18 cruises each year to understand temporal variability in ocean biogeochemistry. On each cruise, the data range from chemical analyses of discrete water samples to data from electronic packages of hydrographic and optics sensors. In addition, a range of biological and geochemical rate measurements are conducted that integrate over time-periods of minutes to days. This sampling strategy yields a reasonable resolution of the major seasonal patterns and of decadal scale variability. The Sargasso Sea also has a variety of episodic production events on scales of days to weeks and these are only poorly resolved. In addition, there is a substantial amount of mesoscale variability in this region and some of the perceived temporal patterns are caused by the intersection of the biweekly sampling with the natural spatial variability. In the Bermuda time-series programs, we have added a series of additional cruises to begin to assess these other sources of variation and their impacts on the interpretation of the main time-series record. However, the adequate resolution of higher frequency temporal patterns will probably require the introduction of new sampling strategies and some emerging technologies such as biogeochemical moorings and autonomous underwater vehicles.
A study of dorsal vein pattern for biometric security

African Journals Online (AJOL)

Nafiisah

ensure more reliable security, many biometric verification techniques have been developed .... 3.0 HA D DORSAL VEI PATTER AS A BIOMETRIC ... image for the back of the hand, and converted by a computer into a digital image that can be.
Evaluation methodologies for security testing biometric systems beyond technological evaluation

OpenAIRE

Fernández Saavedra, María Belén

2013-01-01

The main objective of this PhD Thesis is the specification of formal evaluation methodologies for testing the security level achieved by biometric systems when these are working under specific contour conditions. This analysis is conducted through the calculation of the basic technical biometric system performance and its possible variations. To that end, the next two relevant contributions have been developed. The first contribution is the definition of two independent biometric performance ...
Correlation between fetal mild ventriculomegaly and biometric parameters.

Science.gov (United States)

Fishel-Bartal, Michal; Shai, Daniel; Shina, Avi; Achiron, Reuven; Katorza, Eldad

2017-09-19

The aim of this study was to assess the correlation between fetal lateral ventricle width and biometric measurements. A prospective study on 335 fetuses, 101 fetuses with isolated mild ventriculomegaly and a control group of 234 fetuses with a normal US examination. All fetuses underwent a detailed brain ultrasound scan and a full biometric evaluation. To further compare biometric parameters, we matched, according to gestational week and gender, 91 fetuses from the study group to 91 fetuses from the control group. The mean gestational week during the exam was significantly different between the groups (29.6 weeks in the study group versus 28.3 in the control group, p = .001). The mean maternal age, obstetrical history, mode of conception, or fetal gender did not differ between the groups. After matching according to gestational age and fetal gender, the mean gestational week between the matched groups did not differ and was 29 + 5 weeks in both groups. The study group had significantly larger head circumference (p = .009), biparietal diameter (p biometric measurements and does not necessarily mean a pathological condition.
Multivariate Time Series Decomposition into Oscillation Components.

Science.gov (United States)

Matsuda, Takeru; Komaki, Fumiyasu

2017-08-01

Many time series are considered to be a superposition of several oscillation components. We have proposed a method for decomposing univariate time series into oscillation components and estimating their phases (Matsuda & Komaki, 2017 ). In this study, we extend that method to multivariate time series. We assume that several oscillators underlie the given multivariate time series and that each variable corresponds to a superposition of the projections of the oscillators. Thus, the oscillators superpose on each variable with amplitude and phase modulation. Based on this idea, we develop gaussian linear state-space models and use them to decompose the given multivariate time series. The model parameters are estimated from data using the empirical Bayes method, and the number of oscillators is determined using the Akaike information criterion. Therefore, the proposed method extracts underlying oscillators in a data-driven manner and enables investigation of phase dynamics in a given multivariate time series. Numerical results show the effectiveness of the proposed method. From monthly mean north-south sunspot number data, the proposed method reveals an interesting phase relationship.
Biometric feature extraction using local fractal auto-correlation

International Nuclear Information System (INIS)

Chen Xi; Zhang Jia-Shu

2014-01-01

Image texture feature extraction is a classical means for biometric recognition. To extract effective texture feature for matching, we utilize local fractal auto-correlation to construct an effective image texture descriptor. Three main steps are involved in the proposed scheme: (i) using two-dimensional Gabor filter to extract the texture features of biometric images; (ii) calculating the local fractal dimension of Gabor feature under different orientations and scales using fractal auto-correlation algorithm; and (iii) linking the local fractal dimension of Gabor feature under different orientations and scales into a big vector for matching. Experiments and analyses show our proposed scheme is an efficient biometric feature extraction approach. (condensed matter: structural, mechanical, and thermal properties)

Forecasting Enrollments with Fuzzy Time Series.

Science.gov (United States)

Song, Qiang; Chissom, Brad S.

The concept of fuzzy time series is introduced and used to forecast the enrollment of a university. Fuzzy time series, an aspect of fuzzy set theory, forecasts enrollment using a first-order time-invariant model. To evaluate the model, the conventional linear regression technique is applied and the predicted values obtained are compared to the…
Error checking and near matching in helper data systems for biometric authentication

NARCIS (Netherlands)

Papatsimpa, Charikleia; Linnartz, Jean-Paul; de Groot, Joep; Skoric, B.; Ignatenko, T.

2014-01-01

Helper data systems mitigate the risk that biometric templates are stolen from a biometric data base. Yet, current systems face the drawback that strong Error Correction is needed in order to mitigate variations in the measured biometric during verification. Error correction codes are not always
Forecasting Cryptocurrencies Financial Time Series

DEFF Research Database (Denmark)

Catania, Leopoldo; Grassi, Stefano; Ravazzolo, Francesco

2018-01-01

This paper studies the predictability of cryptocurrencies time series. We compare several alternative univariate and multivariate models in point and density forecasting of four of the most capitalized series: Bitcoin, Litecoin, Ripple and Ethereum. We apply a set of crypto–predictors and rely...
Forecasting Cryptocurrencies Financial Time Series

OpenAIRE

Catania, Leopoldo; Grassi, Stefano; Ravazzolo, Francesco

2018-01-01

This paper studies the predictability of cryptocurrencies time series. We compare several alternative univariate and multivariate models in point and density forecasting of four of the most capitalized series: Bitcoin, Litecoin, Ripple and Ethereum. We apply a set of crypto–predictors and rely on Dynamic Model Averaging to combine a large set of univariate Dynamic Linear Models and several multivariate Vector Autoregressive models with different forms of time variation. We find statistical si...
Dependency of magnetocardiographically determined fetal cardiac time intervals on gestational age, gender and postnatal biometrics in healthy pregnancies

Directory of Open Access Journals (Sweden)

Geue Daniel

2004-04-01

Full Text Available Abstract Background Magnetocardiography enables the precise determination of fetal cardiac time intervals (CTI as early as the second trimester of pregnancy. It has been shown that fetal CTI change in course of gestation. The aim of this work was to investigate the dependency of fetal CTI on gestational age, gender and postnatal biometric data in a substantial sample of subjects during normal pregnancy. Methods A total of 230 fetal magnetocardiograms were obtained in 47 healthy fetuses between the 15th and 42nd week of gestation. In each recording, after subtraction of the maternal cardiac artifact and the identification of fetal beats, fetal PQRST courses were signal averaged. On the basis of therein detected wave onsets and ends, the following CTI were determined: P wave, PR interval, PQ interval, QRS complex, ST segment, T wave, QT and QTc interval. Using regression analysis, the dependency of the CTI were examined with respect to gestational age, gender and postnatal biometric data. Results Atrioventricular conduction and ventricular depolarization times could be determined dependably whereas the T wave was often difficult to detect. Linear and nonlinear regression analysis established strong dependency on age for the P wave and QRS complex (r2 = 0.67, p r2 = 0.66, p r2 = 0.21, p r2 = 0.13, p st week onward (p Conclusion We conclude that 1 from approximately the 18th week to term, fetal CTI which quantify depolarization times can be reliably determined using magnetocardiography, 2 the P wave and QRS complex duration show a high dependency on age which to a large part reflects fetal growth and 3 fetal gender plays a role in QRS complex duration in the third trimester. Fetal development is thus in part reflected in the CTI and may be useful in the identification of intrauterine growth retardation.
Retinal biometrics based on Iterative Closest Point algorithm.

Science.gov (United States)

Hatanaka, Yuji; Tajima, Mikiya; Kawasaki, Ryo; Saito, Koko; Ogohara, Kazunori; Muramatsu, Chisako; Sunayama, Wataru; Fujita, Hiroshi

2017-07-01

The pattern of blood vessels in the eye is unique to each person because it rarely changes over time. Therefore, it is well known that retinal blood vessels are useful for biometrics. This paper describes a biometrics method using the Jaccard similarity coefficient (JSC) based on blood vessel regions in retinal image pairs. The retinal image pairs were rough matched by the center of their optic discs. Moreover, the image pairs were aligned using the Iterative Closest Point algorithm based on detailed blood vessel skeletons. For registration, perspective transform was applied to the retinal images. Finally, the pairs were classified as either correct or incorrect using the JSC of the blood vessel region in the image pairs. The proposed method was applied to temporal retinal images, which were obtained in 2009 (695 images) and 2013 (87 images). The 87 images acquired in 2013 were all from persons already examined in 2009. The accuracy of the proposed method reached 100%.
Time series modeling, computation, and inference

CERN Document Server

Prado, Raquel

2010-01-01

The authors systematically develop a state-of-the-art analysis and modeling of time series. … this book is well organized and well written. The authors present various statistical models for engineers to solve problems in time series analysis. Readers no doubt will learn state-of-the-art techniques from this book.-Hsun-Hsien Chang, Computing Reviews, March 2012My favorite chapters were on dynamic linear models and vector AR and vector ARMA models.-William Seaver, Technometrics, August 2011… a very modern entry to the field of time-series modelling, with a rich reference list of the current lit
Time Series Analysis Forecasting and Control

CERN Document Server

Box, George E P; Reinsel, Gregory C

2011-01-01

A modernized new edition of one of the most trusted books on time series analysis. Since publication of the first edition in 1970, Time Series Analysis has served as one of the most influential and prominent works on the subject. This new edition maintains its balanced presentation of the tools for modeling and analyzing time series and also introduces the latest developments that have occurred n the field over the past decade through applications from areas such as business, finance, and engineering. The Fourth Edition provides a clearly written exploration of the key methods for building, cl
BioTwist : overcoming severe distortions in ridge-based biometrics for succesful identification

NARCIS (Netherlands)

Kotzerke, J.

2016-01-01

This thesis focuses on ridge-based and highly distorted biometrics, the different chal-lenges involved in a verification of identity scenario, and how to overcome them. More specifically, we work on ridge-based biometrics in two different contexts: (i) newborn and infant biometrics and (ii) quality
MULTIMODAL BIOMETRIC AUTHENTICATION USING PARTICLE SWARM OPTIMIZATION ALGORITHM WITH FINGERPRINT AND IRIS

Directory of Open Access Journals (Sweden)

A. Muthukumar

2012-02-01

Full Text Available In general, the identification and verification are done by passwords, pin number, etc., which is easily cracked by others. In order to overcome this issue biometrics is a unique tool for authenticate an individual person. Nevertheless, unimodal biometric is suffered due to noise, intra class variations, spoof attacks, non-universality and some other attacks. In order to avoid these attacks, the multimodal biometrics i.e. combining of more modalities is adapted. In a biometric authentication system, the acceptance or rejection of an entity is dependent on the similarity score falling above or below the threshold. Hence this paper has focused on the security of the biometric system, because compromised biometric templates cannot be revoked or reissued and also this paper has proposed a multimodal system based on an evolutionary algorithm, Particle Swarm Optimization that adapts for varying security environments. With these two concerns, this paper had developed a design incorporating adaptability, authenticity and security.
Costationarity of Locally Stationary Time Series Using costat

OpenAIRE

Cardinali, Alessandro; Nason, Guy P.

2013-01-01

This article describes the R package costat. This package enables a user to (i) perform a test for time series stationarity; (ii) compute and plot time-localized autocovariances, and (iii) to determine and explore any costationary relationship between two locally stationary time series. Two locally stationary time series are said to be costationary if there exists two time-varying combination functions such that the linear combination of the two series with the functions produces another time...
Issues in Biometric Security

African Journals Online (AJOL)

Ogechukwu Iloanusi

Human recognition is required for certain ... automated systems is that some can be stolen, passwords and PIN ... WORKS. A biometric system can be viewed as a simple diagram in figure 1. ... Feature extraction is done with the help of some.
Detecting nonlinear structure in time series

International Nuclear Information System (INIS)

Theiler, J.

1991-01-01

We describe an approach for evaluating the statistical significance of evidence for nonlinearity in a time series. The formal application of our method requires the careful statement of a null hypothesis which characterizes a candidate linear process, the generation of an ensemble of ''surrogate'' data sets which are similar to the original time series but consistent with the null hypothesis, and the computation of a discriminating statistic for the original and for each of the surrogate data sets. The idea is to test the original time series against the null hypothesis by checking whether the discriminating statistic computed for the original time series differs significantly from the statistics computed for each of the surrogate sets. While some data sets very cleanly exhibit low-dimensional chaos, there are many cases where the evidence is sketchy and difficult to evaluate. We hope to provide a framework within which such claims of nonlinearity can be evaluated. 5 refs., 4 figs
Introduction to time series and forecasting

CERN Document Server

Brockwell, Peter J

2016-01-01

This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied to economics, engineering and the natural and social sciences. It assumes knowledge only of basic calculus, matrix algebra and elementary statistics. This third edition contains detailed instructions for the use of the professional version of the Windows-based computer package ITSM2000, now available as a free download from the Springer Extras website. The logic and tools of time series model-building are developed in detail. Numerous exercises are included and the software can be used to analyze and forecast data sets of the user's own choosing. The book can also be used in conjunction with other time series packages such as those included in R. The programs in ITSM2000 however are menu-driven and can be used with minimal investment of time in the computational details. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space mod...
Transforming Security Screening With Biometrics

National Research Council Canada - National Science Library

Hearnsberger, Brian J

2003-01-01

... and identity theft to dramatically improve physical security. Today, biometric technology could be implemented to transform physical security by enhancing screening procedures currently in use at U.S...
Tongue prints: A novel biometric and potential forensic tool.

Science.gov (United States)

Radhika, T; Jeddy, Nadeem; Nithya, S

2016-01-01

Tongue is a vital internal organ well encased within the oral cavity and protected from the environment. It has unique features which differ from individual to individual and even between identical twins. The color, shape, and surface features are characteristic of every individual, and this serves as a tool for identification. Many modes of biometric systems have come into existence such as fingerprint, iris scan, skin color, signature verification, voice recognition, and face recognition. The search for a new personal identification method secure has led to the use of the lingual impression or the tongue print as a method of biometric authentication. Tongue characteristics exhibit sexual dimorphism thus aiding in the identification of the person. Emerging as a novel biometric tool, tongue prints also hold the promise of a potential forensic tool. This review highlights the uniqueness of tongue prints and its superiority over other biometric identification systems. The various methods of tongue print collection and the classification of tongue features are also elucidated.
Application of Some Biometric Indices in the Assessment of the ...

African Journals Online (AJOL)

Application of Some Biometric Indices in the Assessment of the Water Quality of the Benin River, Niger Delta, Nigeria. ... Username, Password, Remember me, or Register ... Rapid Bioassessment Protocols (RBP) using some biometric indices ...
A relation between irreversibility and unlinkability for biometric template protection algorithms

OpenAIRE

井沼, 学

2014-01-01

For biometric recognition systems, privacy protection of enrolled users’ biometric information, which are called biometric templates, is a critical problem. Recently, various template protection algorithms have been proposed and many related previous works have discussed security notions to evaluate the protection performance of these protection algorithms. Irreversibility and unlinkability are important security notions discussed in many related previous works. In this paper, we prove that u...
Biometrics Research and Engineering Laboratory

Data.gov (United States)

Federal Laboratory Consortium — As the Department of Defense moves forward in its pursuit of integrating biometrics technology into facility access control, the Global War on Terrorism and weapon...
Practical considerations in privacy preserving biometric face recognition algorithms

NARCIS (Netherlands)

Papatsimpa, Ch.; de Groot, J.; Linnartz, J.-P.

2013-01-01

The popularity of authentication via fingerprints, iris, face or other biometric features is growing. Hence there is an increasing need to allow a wide variety of verifying parties to have access to biometric template (or reference) data. In this paper, we discuss solutions to ensure that in a

TIME SERIES ANALYSIS USING A UNIQUE MODEL OF TRANSFORMATION

Directory of Open Access Journals (Sweden)

Goran Klepac

2007-12-01

Full Text Available REFII1 model is an authorial mathematical model for time series data mining. The main purpose of that model is to automate time series analysis, through a unique transformation model of time series. An advantage of this approach of time series analysis is the linkage of different methods for time series analysis, linking traditional data mining tools in time series, and constructing new algorithms for analyzing time series. It is worth mentioning that REFII model is not a closed system, which means that we have a finite set of methods. At first, this is a model for transformation of values of time series, which prepares data used by different sets of methods based on the same model of transformation in a domain of problem space. REFII model gives a new approach in time series analysis based on a unique model of transformation, which is a base for all kind of time series analysis. The advantage of REFII model is its possible application in many different areas such as finance, medicine, voice recognition, face recognition and text mining.
A SCHEME FOR TEMPLATE SECURITY AT FEATURE FUSION LEVEL IN MULTIMODAL BIOMETRIC SYSTEM

Directory of Open Access Journals (Sweden)

Arvind Selwal

2016-09-01

Full Text Available Biometric is the science of human recognition based upon using their biological, chemical or behavioural traits. These systems are used in many real life applications simply from biometric based attendance system to providing security at very sophisticated level. A biometric system deals with raw data captured using a sensor and feature template extracted from raw image. One of the challenges being faced by designers of these systems is to secure template data extracted from the biometric modalities of the user and protect the raw images. To minimize spoof attacks on biometric systems by unauthorised users one of the solutions is to use multi-biometric systems. Multi-modal biometric system works by using fusion technique to merge feature templates generated from different modalities of the human. In this work a new scheme is proposed to secure template during feature fusion level. Scheme is based on union operation of fuzzy relations of templates of modalities during fusion process of multimodal biometric systems. This approach serves dual purpose of feature fusion as well as transformation of templates into a single secured non invertible template. The proposed technique is cancelable and experimentally tested on a bimodal biometric system comprising of fingerprint and hand geometry. Developed scheme removes the problem of an attacker learning the original minutia position in fingerprint and various measurements of hand geometry. Given scheme provides improved performance of the system with reduction in false accept rate and improvement in genuine accept rate.
Frontiers in Time Series and Financial Econometrics

OpenAIRE

Ling, S.; McAleer, M.J.; Tong, H.

2015-01-01

__Abstract__ Two of the fastest growing frontiers in econometrics and quantitative finance are time series and financial econometrics. Significant theoretical contributions to financial econometrics have been made by experts in statistics, econometrics, mathematics, and time series analysis. The purpose of this special issue of the journal on “Frontiers in Time Series and Financial Econometrics” is to highlight several areas of research by leading academics in which novel methods have contrib...
Hand-Based Biometric Analysis

Science.gov (United States)

Bebis, George (Inventor); Amayeh, Gholamreza (Inventor)

2015-01-01

Hand-based biometric analysis systems and techniques are described which provide robust hand-based identification and verification. An image of a hand is obtained, which is then segmented into a palm region and separate finger regions. Acquisition of the image is performed without requiring particular orientation or placement restrictions. Segmentation is performed without the use of reference points on the images. Each segment is analyzed by calculating a set of Zernike moment descriptors for the segment. The feature parameters thus obtained are then fused and compared to stored sets of descriptors in enrollment templates to arrive at an identity decision. By using Zernike moments, and through additional manipulation, the biometric analysis is invariant to rotation, scale, or translation or an in put image. Additionally, the analysis utilizes re-use of commonly-seen terms in Zernike calculations to achieve additional efficiencies over traditional Zernike moment calculation.
Scale-dependent intrinsic entropies of complex time series.

Science.gov (United States)

Yeh, Jia-Rong; Peng, Chung-Kang; Huang, Norden E

2016-04-13

Multi-scale entropy (MSE) was developed as a measure of complexity for complex time series, and it has been applied widely in recent years. The MSE algorithm is based on the assumption that biological systems possess the ability to adapt and function in an ever-changing environment, and these systems need to operate across multiple temporal and spatial scales, such that their complexity is also multi-scale and hierarchical. Here, we present a systematic approach to apply the empirical mode decomposition algorithm, which can detrend time series on various time scales, prior to analysing a signal's complexity by measuring the irregularity of its dynamics on multiple time scales. Simulated time series of fractal Gaussian noise and human heartbeat time series were used to study the performance of this new approach. We show that our method can successfully quantify the fractal properties of the simulated time series and can accurately distinguish modulations in human heartbeat time series in health and disease. © 2016 The Author(s).
Elements of nonlinear time series analysis and forecasting

CERN Document Server

De Gooijer, Jan G

2017-01-01

This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications. Avoiding a “theorem-proof” format, it shows concrete applications on a variety of empirical time series. The book can be used in graduate courses in nonlinear time series and at the same time also includes interesting material for more advanced readers. Though it is largely self-contained, readers require an understanding of basic linear time series concepts, Markov chains and Monte Carlo simulation methods. The book covers time-domain and frequency-domain methods for the analysis of both univariate and multivariate (vector) time series. It makes a clear distinction between parametric models on the one hand, and semi- and nonparametric models/methods on the other. This offers the reader the option of concentrating exclusively on one of these nonlinear time series analysis methods. To make the book as user friendly as possible...
An Energy-Based Similarity Measure for Time Series

Directory of Open Access Journals (Sweden)

Pierre Brunagel

2007-11-01

Full Text Available A new similarity measure, called SimilB, for time series analysis, based on the cross-ÃŽÂ¨B-energy operator (2004, is introduced. ÃŽÂ¨B is a nonlinear measure which quantifies the interaction between two time series. Compared to Euclidean distance (ED or the Pearson correlation coefficient (CC, SimilB includes the temporal information and relative changes of the time series using the first and second derivatives of the time series. SimilB is well suited for both nonstationary and stationary time series and particularly those presenting discontinuities. Some new properties of ÃŽÂ¨B are presented. Particularly, we show that ÃŽÂ¨B as similarity measure is robust to both scale and time shift. SimilB is illustrated with synthetic time series and an artificial dataset and compared to the CC and the ED measures.
Biometric template data protection in mobile device environment using XML-database

DEFF Research Database (Denmark)

Thirumathyam, Rubathas; Derawi, Mohammad; Fischer, Paul

2010-01-01

recognition or gait recognition. To gain a real understanding of how it is possible to protect the biometric data, this paper first starts out with introducing a technique for security in a biometric system and emphasizes that template protection is important by going through the vulnerabilities and threats....... Furthermore, it points out requirements for template protection, a recital of various template protection schemes and a brief overview of biometric standards....
Study on a Biometric Authentication Model based on ECG using a Fuzzy Neural Network

Science.gov (United States)

Kim, Ho J.; Lim, Joon S.

2018-03-01

Traditional authentication methods use numbers or graphic passwords and thus involve the risk of loss or theft. Various studies are underway regarding biometric authentication because it uses the unique biometric data of a human being. Biometric authentication technology using ECG from biometric data involves signals that record electrical stimuli from the heart. It is difficult to manipulate and is advantageous in that it enables unrestrained measurements from sensors that are attached to the skin. This study is on biometric authentication methods using the neural network with weighted fuzzy membership functions (NEWFM). In the biometric authentication process, normalization and the ensemble average is applied during preprocessing, characteristics are extracted using Haar-wavelets, and a registration process called “training” is performed in the fuzzy neural network. In the experiment, biometric authentication was performed on 73 subjects in the Physionet Database. 10-40 ECG waveforms were tested for use in the registration process, and 15 ECG waveforms were deemed the appropriate number for registering ECG waveforms. 1 ECG waveforms were used during the authentication stage to conduct the biometric authentication test. Upon testing the proposed biometric authentication method based on 73 subjects from the Physionet Database, the TAR was 98.32% and FAR was 5.84%.
Detecting chaos in irregularly sampled time series.

Science.gov (United States)

Kulp, C W

2013-09-01

Recently, Wiebe and Virgin [Chaos 22, 013136 (2012)] developed an algorithm which detects chaos by analyzing a time series' power spectrum which is computed using the Discrete Fourier Transform (DFT). Their algorithm, like other time series characterization algorithms, requires that the time series be regularly sampled. Real-world data, however, are often irregularly sampled, thus, making the detection of chaotic behavior difficult or impossible with those methods. In this paper, a characterization algorithm is presented, which effectively detects chaos in irregularly sampled time series. The work presented here is a modification of Wiebe and Virgin's algorithm and uses the Lomb-Scargle Periodogram (LSP) to compute a series' power spectrum instead of the DFT. The DFT is not appropriate for irregularly sampled time series. However, the LSP is capable of computing the frequency content of irregularly sampled data. Furthermore, a new method of analyzing the power spectrum is developed, which can be useful for differentiating between chaotic and non-chaotic behavior. The new characterization algorithm is successfully applied to irregularly sampled data generated by a model as well as data consisting of observations of variable stars.
Building Chaotic Model From Incomplete Time Series

Science.gov (United States)

Siek, Michael; Solomatine, Dimitri

2010-05-01

This paper presents a number of novel techniques for building a predictive chaotic model from incomplete time series. A predictive chaotic model is built by reconstructing the time-delayed phase space from observed time series and the prediction is made by a global model or adaptive local models based on the dynamical neighbors found in the reconstructed phase space. In general, the building of any data-driven models depends on the completeness and quality of the data itself. However, the completeness of the data availability can not always be guaranteed since the measurement or data transmission is intermittently not working properly due to some reasons. We propose two main solutions dealing with incomplete time series: using imputing and non-imputing methods. For imputing methods, we utilized the interpolation methods (weighted sum of linear interpolations, Bayesian principle component analysis and cubic spline interpolation) and predictive models (neural network, kernel machine, chaotic model) for estimating the missing values. After imputing the missing values, the phase space reconstruction and chaotic model prediction are executed as a standard procedure. For non-imputing methods, we reconstructed the time-delayed phase space from observed time series with missing values. This reconstruction results in non-continuous trajectories. However, the local model prediction can still be made from the other dynamical neighbors reconstructed from non-missing values. We implemented and tested these methods to construct a chaotic model for predicting storm surges at Hoek van Holland as the entrance of Rotterdam Port. The hourly surge time series is available for duration of 1990-1996. For measuring the performance of the proposed methods, a synthetic time series with missing values generated by a particular random variable to the original (complete) time series is utilized. There exist two main performance measures used in this work: (1) error measures between the actual
Normalizing Electrocardiograms of Both Healthy Persons and Cardiovascular Disease Patients for Biometric Authentication

Science.gov (United States)

Zhao, Miaomiao; Li, Fan; Wang, Guoqing; Zhou, Fengfeng

2013-01-01

Although electrocardiogram (ECG) fluctuates over time and physical activity, some of its intrinsic measurements serve well as biometric features. Considering its constant availability and difficulty in being faked, the ECG signal is becoming a promising factor for biometric authentication. The majority of the currently available algorithms only work well on healthy participants. A novel normalization and interpolation algorithm is proposed to convert an ECG signal into multiple template cycles, which are comparable between any two ECGs, no matter the sampling rates or health status. The overall accuracies reach 100% and 90.11% for healthy participants and cardiovascular disease (CVD) patients, respectively. PMID:23977063
Multivariate Time Series Search

Data.gov (United States)

National Aeronautics and Space Administration — Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical...
Analysing Stable Time Series

National Research Council Canada - National Science Library

Adler, Robert

1997-01-01

We describe how to take a stable, ARMA, time series through the various stages of model identification, parameter estimation, and diagnostic checking, and accompany the discussion with a goodly number...
Biometric Analysis of Hunteria umbellata (K.Schum.) Hallier f and ...

African Journals Online (AJOL)

Biometric Analysis of Hunteria umbellata (K.Schum.) ... Username, Password, Remember me, or Register ... The biometric analysis of data from five diabetic patients that were placed on herbal treatment were taken daily for a period of 3 weeks ...
Neural Network Models for Time Series Forecasts

OpenAIRE

Tim Hill; Marcus O'Connor; William Remus

1996-01-01

Neural networks have been advocated as an alternative to traditional statistical forecasting methods. In the present experiment, time series forecasts produced by neural networks are compared with forecasts from six statistical time series methods generated in a major forecasting competition (Makridakis et al. [Makridakis, S., A. Anderson, R. Carbone, R. Fildes, M. Hibon, R. Lewandowski, J. Newton, E. Parzen, R. Winkler. 1982. The accuracy of extrapolation (time series) methods: Results of a ...
Biometric identification based on novel frequency domain facial asymmetry measures

Science.gov (United States)

Mitra, Sinjini; Savvides, Marios; Vijaya Kumar, B. V. K.

2005-03-01

In the modern world, the ever-growing need to ensure a system's security has spurred the growth of the newly emerging technology of biometric identification. The present paper introduces a novel set of facial biometrics based on quantified facial asymmetry measures in the frequency domain. In particular, we show that these biometrics work well for face images showing expression variations and have the potential to do so in presence of illumination variations as well. A comparison of the recognition rates with those obtained from spatial domain asymmetry measures based on raw intensity values suggests that the frequency domain representation is more robust to intra-personal distortions and is a novel approach for performing biometric identification. In addition, some feature analysis based on statistical methods comparing the asymmetry measures across different individuals and across different expressions is presented.
Multiple-stage pure phase encoding with biometric information

Science.gov (United States)

Chen, Wen

2018-01-01

In recent years, many optical systems have been developed for securing information, and optical encryption/encoding has attracted more and more attention due to the marked advantages, such as parallel processing and multiple-dimensional characteristics. In this paper, an optical security method is presented based on pure phase encoding with biometric information. Biometric information (such as fingerprint) is employed as security keys rather than plaintext used in conventional optical security systems, and multiple-stage phase-encoding-based optical systems are designed for generating several phase-only masks with biometric information. Subsequently, the extracted phase-only masks are further used in an optical setup for encoding an input image (i.e., plaintext). Numerical simulations are conducted to illustrate the validity, and the results demonstrate that high flexibility and high security can be achieved.
Binary Biometrics: An Analytic Framework to Estimate the Performance Curves Under Gaussian Assumption

NARCIS (Netherlands)

Kelkboom, E.J.C.; Garcia Molina, Gary; Breebaart, Jeroen; Veldhuis, Raymond N.J.; Kevenaar, Tom A.M.; Jonker, Willem

In recent years, the protection of biometric data has gained increased interest from the scientific community. Methods such as the fuzzy commitment scheme, helper-data system, fuzzy extractors, fuzzy vault, and cancelable biometrics have been proposed for protecting biometric data. Most of these
Time Series Observations in the North Indian Ocean

Digital Repository Service at National Institute of Oceanography (India)

Shenoy, D.M.; Naik, H.; Kurian, S.; Naqvi, S.W.A.; Khare, N.

Ocean and the ongoing time series study (Candolim Time Series; CaTS) off Goa. In addition, this article also focuses on the new time series initiative in the Arabian Sea and the Bay of Bengal under Sustained Indian Ocean Biogeochemistry and Ecosystem...

A SCHEME FOR TEMPLATE SECURITY AT FEATURE FUSION LEVEL IN MULTIMODAL BIOMETRIC SYSTEM

OpenAIRE

Arvind Selwal; Sunil Kumar Gupta; Surender Kumar

2016-01-01

Biometric is the science of human recognition based upon using their biological, chemical or behavioural traits. These systems are used in many real life applications simply from biometric based attendance system to providing security at very sophisticated level. A biometric system deals with raw data captured using a sensor and feature template extracted from raw image. One of the challenges being faced by designers of these systems is to secure template data extracted from the biometric mod...
Geometric noise reduction for multivariate time series.

Science.gov (United States)

Mera, M Eugenia; Morán, Manuel

2006-03-01

We propose an algorithm for the reduction of observational noise in chaotic multivariate time series. The algorithm is based on a maximum likelihood criterion, and its goal is to reduce the mean distance of the points of the cleaned time series to the attractor. We give evidence of the convergence of the empirical measure associated with the cleaned time series to the underlying invariant measure, implying the possibility to predict the long run behavior of the true dynamics.
BRITS: Bidirectional Recurrent Imputation for Time Series

OpenAIRE

Cao, Wei; Wang, Dong; Li, Jian; Zhou, Hao; Li, Lei; Li, Yitan

2018-01-01

Time series are widely used as signals in many classification/regression tasks. It is ubiquitous that time series contains many missing values. Given multiple correlated time series data, how to fill in missing values and to predict their class labels? Existing imputation methods often impose strong assumptions of the underlying data generating process, such as linear dynamics in the state space. In this paper, we propose BRITS, a novel method based on recurrent neural networks for missing va...
Efficient Algorithms for Segmentation of Item-Set Time Series

Science.gov (United States)

Chundi, Parvathi; Rosenkrantz, Daniel J.

We propose a special type of time series, which we call an item-set time series, to facilitate the temporal analysis of software version histories, email logs, stock market data, etc. In an item-set time series, each observed data value is a set of discrete items. We formalize the concept of an item-set time series and present efficient algorithms for segmenting a given item-set time series. Segmentation of a time series partitions the time series into a sequence of segments where each segment is constructed by combining consecutive time points of the time series. Each segment is associated with an item set that is computed from the item sets of the time points in that segment, using a function which we call a measure function. We then define a concept called the segment difference, which measures the difference between the item set of a segment and the item sets of the time points in that segment. The segment difference values are required to construct an optimal segmentation of the time series. We describe novel and efficient algorithms to compute segment difference values for each of the measure functions described in the paper. We outline a dynamic programming based scheme to construct an optimal segmentation of the given item-set time series. We use the item-set time series segmentation techniques to analyze the temporal content of three different data sets—Enron email, stock market data, and a synthetic data set. The experimental results show that an optimal segmentation of item-set time series data captures much more temporal content than a segmentation constructed based on the number of time points in each segment, without examining the item set data at the time points, and can be used to analyze different types of temporal data.
Studies on time series applications in environmental sciences

CERN Document Server

Bărbulescu, Alina

2016-01-01

Time series analysis and modelling represent a large study field, implying the approach from the perspective of the time and frequency, with applications in different domains. Modelling hydro-meteorological time series is difficult due to the characteristics of these series, as long range dependence, spatial dependence, the correlation with other series. Continuous spatial data plays an important role in planning, risk assessment and decision making in environmental management. In this context, in this book we present various statistical tests and modelling techniques used for time series analysis, as well as applications to hydro-meteorological series from Dobrogea, a region situated in the south-eastern part of Romania, less studied till now. Part of the results are accompanied by their R code. .
Global Population Density Grid Time Series Estimates

Data.gov (United States)

National Aeronautics and Space Administration — Global Population Density Grid Time Series Estimates provide a back-cast time series of population density grids based on the year 2000 population grid from SEDAC's...
Prediction and Geometry of Chaotic Time Series

National Research Council Canada - National Science Library

Leonardi, Mary

1997-01-01

This thesis examines the topic of chaotic time series. An overview of chaos, dynamical systems, and traditional approaches to time series analysis is provided, followed by an examination of state space reconstruction...
Strategies for Exploiting Independent Cloud Implementations of Biometric Experts in Multibiometric Scenarios

Directory of Open Access Journals (Sweden)

P. Peer

2014-01-01

Full Text Available Cloud computing represents one of the fastest growing areas of technology and offers a new computing model for various applications and services. This model is particularly interesting for the area of biometric recognition, where scalability, processing power, and storage requirements are becoming a bigger and bigger issue with each new generation of recognition technology. Next to the availability of computing resources, another important aspect of cloud computing with respect to biometrics is accessibility. Since biometric cloud services are easily accessible, it is possible to combine different existing implementations and design new multibiometric services that next to almost unlimited resources also offer superior recognition performance and, consequently, ensure improved security to its client applications. Unfortunately, the literature on the best strategies of how to combine existing implementations of cloud-based biometric experts into a multibiometric service is virtually nonexistent. In this paper, we try to close this gap and evaluate different strategies for combining existing biometric experts into a multibiometric cloud service. We analyze the (fusion strategies from different perspectives such as performance gains, training complexity, or resource consumption and present results and findings important to software developers and other researchers working in the areas of biometrics and cloud computing. The analysis is conducted based on two biometric cloud services, which are also presented in the paper.
On the feasibility of interoperable schemes in hand biometrics.

Science.gov (United States)

Morales, Aythami; González, Ester; Ferrer, Miguel A

2012-01-01

Personal recognition through hand-based biometrics has attracted the interest of many researchers in the last twenty years. A significant number of proposals based on different procedures and acquisition devices have been published in the literature. However, comparisons between devices and their interoperability have not been thoroughly studied. This paper tries to fill this gap by proposing procedures to improve the interoperability among different hand biometric schemes. The experiments were conducted on a database made up of 8,320 hand images acquired from six different hand biometric schemes, including a flat scanner, webcams at different wavelengths, high quality cameras, and contactless devices. Acquisitions on both sides of the hand were included. Our experiment includes four feature extraction methods which determine the best performance among the different scenarios for two of the most popular hand biometrics: hand shape and palm print. We propose smoothing techniques at the image and feature levels to reduce interdevice variability. Results suggest that comparative hand shape offers better performance in terms of interoperability than palm prints, but palm prints can be more effective when using similar sensors.
Printable, scannable biometric templates for secure documents and materials

Science.gov (United States)

Cambier, James L.; Musgrave, Clyde

2000-04-01

Biometric technology has been widely acknowledged as an effective means for enhancing private and public security through applications in physical access control, computer and computer network access control, medical records protection, banking security, public identification programs, and others. Nearly all of these applications involve use of a biometric token to control access to a physical entity or private information. There are also unique benefits to be derived from attaching a biometric template to a physical entity such as a document, package, laboratory sample, etc. Such an association allows fast, reliable, and highly accurate association of an individual person's identity to the physical entity, and can be used to enhance security, convenience, and privacy in many types of transactions. Examples include authentication of documents, tracking of laboratory samples in a testing environment, monitoring the movement of physical evidence within the criminal justice system, and authenticating the identity of both sending and receiving parties in shipment of high value parcels. A system is described which combines a biometric technology based on iris recognition with a printing and scanning technology for high-density bar codes.
On the Feasibility of Interoperable Schemes in Hand Biometrics

Science.gov (United States)

Morales, Aythami; González, Ester; Ferrer, Miguel A.

2012-01-01

Personal recognition through hand-based biometrics has attracted the interest of many researchers in the last twenty years. A significant number of proposals based on different procedures and acquisition devices have been published in the literature. However, comparisons between devices and their interoperability have not been thoroughly studied. This paper tries to fill this gap by proposing procedures to improve the interoperability among different hand biometric schemes. The experiments were conducted on a database made up of 8,320 hand images acquired from six different hand biometric schemes, including a flat scanner, webcams at different wavelengths, high quality cameras, and contactless devices. Acquisitions on both sides of the hand were included. Our experiment includes four feature extraction methods which determine the best performance among the different scenarios for two of the most popular hand biometrics: hand shape and palm print. We propose smoothing techniques at the image and feature levels to reduce interdevice variability. Results suggest that comparative hand shape offers better performance in terms of interoperability than palm prints, but palm prints can be more effective when using similar sensors. PMID:22438714
Electronic Biometric Transmission Specification. Version 1.2

Science.gov (United States)

2006-11-08

Prescribed by ANSI Std Z39-18 Electronic Biometric Transmission Specification DIN: DOD_BTF_TS_EBTS_ Nov06_01.02.00 i Revision History Revision...contains: • the ORI • a Greenwich Mean (a.k.a. Zulu or UTC) date/time stamp • a code for the software used at the point of collection/transmission...long names and would generally include the tribe name. Subfield 1 Item 1 Character Type AS Characters 1 to 50 Special Characters: Any 7-bit non
Sensor-Generated Time Series Events: A Definition Language

Science.gov (United States)

Anguera, Aurea; Lara, Juan A.; Lizcano, David; Martínez, Maria Aurora; Pazos, Juan

2012-01-01

There are now a great many domains where information is recorded by sensors over a limited time period or on a permanent basis. This data flow leads to sequences of data known as time series. In many domains, like seismography or medicine, time series analysis focuses on particular regions of interest, known as events, whereas the remainder of the time series contains hardly any useful information. In these domains, there is a need for mechanisms to identify and locate such events. In this paper, we propose an events definition language that is general enough to be used to easily and naturally define events in time series recorded by sensors in any domain. The proposed language has been applied to the definition of time series events generated within the branch of medicine dealing with balance-related functions in human beings. A device, called posturograph, is used to study balance-related functions. The platform has four sensors that record the pressure intensity being exerted on the platform, generating four interrelated time series. As opposed to the existing ad hoc proposals, the results confirm that the proposed language is valid, that is generally applicable and accurate, for identifying the events contained in the time series.
Possibilities of dynamic biometrics for authentication and the circumstances for using dynamic biometric signature

Directory of Open Access Journals (Sweden)

Frantisek Hortai

2018-01-01

Full Text Available New information technologies alongside their benefits also bring new dangers with themselves. It is difficult to decide which authentication tool to use and implement in the information systems and electronic documents. The final decision has to compromise among the facts that it faces several conflicting requirements: highly secure tool, to be a user-friendly and user simplicity method, ensure protection against errors and failures of users, speed of authentication and provide these features for a reasonable price. Even when the compromised solution is found it has to fulfill the given technology standards. For the listed reasons the paper argues one of the most natural biometric authentication method the dynamic biometric signature and lists its related standards. The paper also includes measurement evaluation which solves the independence between the person’s signature and device on which it was created
AN APPROACH TO REDUCE THE STORAGE REQUIREMENT FOR BIOMETRIC DATA IN AADHAR PROJECT

Directory of Open Access Journals (Sweden)

T. Sivakumar

2013-02-01

Full Text Available AADHAR is an Indian Government Project to provide unique identification to each Citizen of India. The objective of the project is to collect all the personal details and the biometric traits from each individual. Biometric traits such as iris, face and fingerprint are being collected for authentication. All the information will be stored in a centralized data repository. Considering about the storage requirement for the biometric data of the entire population of India, approximately 20,218 TB of storage space will be required. Since 10 fingerprint data are stored, fingerprint details will take most of the space. In this paper, the storage requirement for the biometric data in the AADHAR project is analyzed and a method is proposed to reduce the storage by cropping the original biometric image before storing. This method can reduce the storage space of the biometric data drastically. All the measurements given in this paper are approximate only.
A biometric authentication model using hand gesture images.

Science.gov (United States)

Fong, Simon; Zhuang, Yan; Fister, Iztok; Fister, Iztok

2013-10-30

A novel hand biometric authentication method based on measurements of the user's stationary hand gesture of hand sign language is proposed. The measurement of hand gestures could be sequentially acquired by a low-cost video camera. There could possibly be another level of contextual information, associated with these hand signs to be used in biometric authentication. As an analogue, instead of typing a password 'iloveu' in text which is relatively vulnerable over a communication network, a signer can encode a biometric password using a sequence of hand signs, 'i' , 'l' , 'o' , 'v' , 'e' , and 'u'. Subsequently the features from the hand gesture images are extracted which are integrally fuzzy in nature, to be recognized by a classification model for telling if this signer is who he claimed himself to be, by examining over his hand shape and the postures in doing those signs. It is believed that everybody has certain slight but unique behavioral characteristics in sign language, so are the different hand shape compositions. Simple and efficient image processing algorithms are used in hand sign recognition, including intensity profiling, color histogram and dimensionality analysis, coupled with several popular machine learning algorithms. Computer simulation is conducted for investigating the efficacy of this novel biometric authentication model which shows up to 93.75% recognition accuracy.
Correlation and multifractality in climatological time series

International Nuclear Information System (INIS)

Pedron, I T

2010-01-01

Climate can be described by statistical analysis of mean values of atmospheric variables over a period. It is possible to detect correlations in climatological time series and to classify its behavior. In this work the Hurst exponent, which can characterize correlation and persistence in time series, is obtained by using the Detrended Fluctuation Analysis (DFA) method. Data series of temperature, precipitation, humidity, solar radiation, wind speed, maximum squall, atmospheric pressure and randomic series are studied. Furthermore, the multifractality of such series is analyzed applying the Multifractal Detrended Fluctuation Analysis (MF-DFA) method. The results indicate presence of correlation (persistent character) in all climatological series and multifractality as well. A larger set of data, and longer, could provide better results indicating the universality of the exponents.
Biometrical analysis in radiobiological works of N.V. Luchnik

International Nuclear Information System (INIS)

Glotov, N.V.

1996-01-01

The contribution of the famous Russian geneticist and biophysics N.V. Luchnik into biometrical analysis of radiobiological data is discussed. His works on radiation mortality of mice (2) and the process of post-radiation repair of chromosome aberrations (10) are thoroughly observed. The conclusion of necessity to develop biometrical analysis as separate part of biometry is made
Time Series Forecasting with Missing Values

Directory of Open Access Journals (Sweden)

Shin-Fu Wu

2015-11-01

Full Text Available Time series prediction has become more popular in various kinds of applications such as weather prediction, control engineering, financial analysis, industrial monitoring, etc. To deal with real-world problems, we are often faced with missing values in the data due to sensor malfunctions or human errors. Traditionally, the missing values are simply omitted or replaced by means of imputation methods. However, omitting those missing values may cause temporal discontinuity. Imputation methods, on the other hand, may alter the original time series. In this study, we propose a novel forecasting method based on least squares support vector machine (LSSVM. We employ the input patterns with the temporal information which is defined as local time index (LTI. Time series data as well as local time indexes are fed to LSSVM for doing forecasting without imputation. We compare the forecasting performance of our method with other imputation methods. Experimental results show that the proposed method is promising and is worth further investigations.
Mathematical and information maintenance of biometric systems

Science.gov (United States)

Boriev, Z.; Sokolov, S.; Nyrkov, A.; Nekrasova, A.

2016-04-01

This article describes the different mathematical methods for processing biometric data. A brief overview of methods for personality recognition by means of a signature is conducted. Mathematical solutions of a dynamic authentication method are considered. Recommendations on use of certain mathematical methods, depending on specific tasks, are provided. Based on the conducted analysis of software and the choice made in favor of the wavelet analysis, a brief basis for its use in the course of software development for biometric personal identification is given for the purpose of its practical application.

Reconstruction of ensembles of coupled time-delay systems from time series.

Science.gov (United States)

Sysoev, I V; Prokhorov, M D; Ponomarenko, V I; Bezruchko, B P

2014-06-01

We propose a method to recover from time series the parameters of coupled time-delay systems and the architecture of couplings between them. The method is based on a reconstruction of model delay-differential equations and estimation of statistical significance of couplings. It can be applied to networks composed of nonidentical nodes with an arbitrary number of unidirectional and bidirectional couplings. We test our method on chaotic and periodic time series produced by model equations of ensembles of diffusively coupled time-delay systems in the presence of noise, and apply it to experimental time series obtained from electronic oscillators with delayed feedback coupled by resistors.
Securing Iris Templates using Combined User and Soft Biometric based Password Hardened Fuzzy Vault

OpenAIRE

Meenakshi, V. S.; Padmavathi, G.

2010-01-01

Personal identification and authentication is very crucial in the current scenario. Biometrics plays an important role in this area. Biometric based authentication has proved superior compared to traditional password based authentication. Anyhow biometrics is permanent feature of a person and cannot be reissued when compromised as passwords. To over come this problem, instead of storing the original biometric templates transformed templates can be stored. Whenever the transformation function ...
Developing a multimodal biometric authentication system using soft computing methods.

Science.gov (United States)

Malcangi, Mario

2015-01-01

Robust personal authentication is becoming ever more important in computer-based applications. Among a variety of methods, biometric offers several advantages, mainly in embedded system applications. Hard and soft multi-biometric, combined with hard and soft computing methods, can be applied to improve the personal authentication process and to generalize the applicability. This chapter describes the embedded implementation of a multi-biometric (voiceprint and fingerprint) multimodal identification system based on hard computing methods (DSP) for feature extraction and matching, an artificial neural network (ANN) for soft feature pattern matching, and a fuzzy logic engine (FLE) for data fusion and decision.
Biometrics Go Mainstream

Science.gov (United States)

Gale, Doug

2006-01-01

Authentication is based on something one knows (e.g., a password), something one has (e.g., a driver's license), or something one is (e.g., a fingerprint). The last of these refers to the use of biometrics for authentication. With the blink of an eye, the touch of a finger, or the uttering of a pass-phrase, colleges and schools can now get deadly…
Atmospheric turbulence and sensor system effects on biometric algorithm performance

Science.gov (United States)

Espinola, Richard L.; Leonard, Kevin R.; Byrd, Kenneth A.; Potvin, Guy

2015-05-01

Biometric technologies composed of electro-optical/infrared (EO/IR) sensor systems and advanced matching algorithms are being used in various force protection/security and tactical surveillance applications. To date, most of these sensor systems have been widely used in controlled conditions with varying success (e.g., short range, uniform illumination, cooperative subjects). However the limiting conditions of such systems have yet to be fully studied for long range applications and degraded imaging environments. Biometric technologies used for long range applications will invariably suffer from the effects of atmospheric turbulence degradation. Atmospheric turbulence causes blur, distortion and intensity fluctuations that can severely degrade image quality of electro-optic and thermal imaging systems and, for the case of biometrics technology, translate to poor matching algorithm performance. In this paper, we evaluate the effects of atmospheric turbulence and sensor resolution on biometric matching algorithm performance. We use a subset of the Facial Recognition Technology (FERET) database and a commercial algorithm to analyze facial recognition performance on turbulence degraded facial images. The goal of this work is to understand the feasibility of long-range facial recognition in degraded imaging conditions, and the utility of camera parameter trade studies to enable the design of the next generation biometrics sensor systems.
The analysis of time series: an introduction

National Research Council Canada - National Science Library

Chatfield, Christopher

1989-01-01

.... A variety of practical examples are given to support the theory. The book covers a wide range of time-series topics, including probability models for time series, Box-Jenkins forecasting, spectral analysis, linear systems and system identification...
Image Quality Assessment for Fake Biometric Detection: Application to Iris, Fingerprint, and Face Recognition.

Science.gov (United States)

Galbally, Javier; Marcel, Sébastien; Fierrez, Julian

2014-02-01

To ensure the actual presence of a real legitimate trait in contrast to a fake self-manufactured synthetic or reconstructed sample is a significant problem in biometric authentication, which requires the development of new and efficient protection measures. In this paper, we present a novel software-based fake detection method that can be used in multiple biometric systems to detect different types of fraudulent access attempts. The objective of the proposed system is to enhance the security of biometric recognition frameworks, by adding liveness assessment in a fast, user-friendly, and non-intrusive manner, through the use of image quality assessment. The proposed approach presents a very low degree of complexity, which makes it suitable for real-time applications, using 25 general image quality features extracted from one image (i.e., the same acquired for authentication purposes) to distinguish between legitimate and impostor samples. The experimental results, obtained on publicly available data sets of fingerprint, iris, and 2D face, show that the proposed method is highly competitive compared with other state-of-the-art approaches and that the analysis of the general image quality of real biometric samples reveals highly valuable information that may be very efficiently used to discriminate them from fake traits.
Time series modeling in traffic safety research.

Science.gov (United States)

Lavrenz, Steven M; Vlahogianni, Eleni I; Gkritza, Konstantina; Ke, Yue

2018-08-01

The use of statistical models for analyzing traffic safety (crash) data has been well-established. However, time series techniques have traditionally been underrepresented in the corresponding literature, due to challenges in data collection, along with a limited knowledge of proper methodology. In recent years, new types of high-resolution traffic safety data, especially in measuring driver behavior, have made time series modeling techniques an increasingly salient topic of study. Yet there remains a dearth of information to guide analysts in their use. This paper provides an overview of the state of the art in using time series models in traffic safety research, and discusses some of the fundamental techniques and considerations in classic time series modeling. It also presents ongoing and future opportunities for expanding the use of time series models, and explores newer modeling techniques, including computational intelligence models, which hold promise in effectively handling ever-larger data sets. The information contained herein is meant to guide safety researchers in understanding this broad area of transportation data analysis, and provide a framework for understanding safety trends that can influence policy-making. Copyright © 2017 Elsevier Ltd. All rights reserved.
Time series prediction: statistical and neural techniques

Science.gov (United States)

Zahirniak, Daniel R.; DeSimio, Martin P.

1996-03-01

In this paper we compare the performance of nonlinear neural network techniques to those of linear filtering techniques in the prediction of time series. Specifically, we compare the results of using the nonlinear systems, known as multilayer perceptron and radial basis function neural networks, with the results obtained using the conventional linear Wiener filter, Kalman filter and Widrow-Hoff adaptive filter in predicting future values of stationary and non- stationary time series. Our results indicate the performance of each type of system is heavily dependent upon the form of the time series being predicted and the size of the system used. In particular, the linear filters perform adequately for linear or near linear processes while the nonlinear systems perform better for nonlinear processes. Since the linear systems take much less time to be developed, they should be tried prior to using the nonlinear systems when the linearity properties of the time series process are unknown.
Effectiveness of Multivariate Time Series Classification Using Shapelets

Directory of Open Access Journals (Sweden)

A. P. Karpenko

2015-01-01

Full Text Available Typically, time series classifiers require signal pre-processing (filtering signals from noise and artifact removal, etc., enhancement of signal features (amplitude, frequency, spectrum, etc., classification of signal features in space using the classical techniques and classification algorithms of multivariate data. We consider a method of classifying time series, which does not require enhancement of the signal features. The method uses the shapelets of time series (time series shapelets i.e. small fragments of this series, which reflect properties of one of its classes most of all.Despite the significant number of publications on the theory and shapelet applications for classification of time series, the task to evaluate the effectiveness of this technique remains relevant. An objective of this publication is to study the effectiveness of a number of modifications of the original shapelet method as applied to the multivariate series classification that is a littlestudied problem. The paper presents the problem statement of multivariate time series classification using the shapelets and describes the shapelet–based basic method of binary classification, as well as various generalizations and proposed modification of the method. It also offers the software that implements a modified method and results of computational experiments confirming the effectiveness of the algorithmic and software solutions.The paper shows that the modified method and the software to use it allow us to reach the classification accuracy of about 85%, at best. The shapelet search time increases in proportion to input data dimension.
Demographic Analysis from Biometric Data: Achievements, Challenges, and New Frontiers.

Science.gov (United States)

Sun, Yunlian; Zhang, Man; Sun, Zhenan; Tan, Tieniu

2018-02-01

Biometrics is the technique of automatically recognizing individuals based on their biological or behavioral characteristics. Various biometric traits have been introduced and widely investigated, including fingerprint, iris, face, voice, palmprint, gait and so forth. Apart from identity, biometric data may convey various other personal information, covering affect, age, gender, race, accent, handedness, height, weight, etc. Among these, analysis of demographics (age, gender, and race) has received tremendous attention owing to its wide real-world applications, with significant efforts devoted and great progress achieved. This survey first presents biometric demographic analysis from the standpoint of human perception, then provides a comprehensive overview of state-of-the-art advances in automated estimation from both academia and industry. Despite these advances, a number of challenging issues continue to inhibit its full potential. We second discuss these open problems, and finally provide an outlook into the future of this very active field of research by sharing some promising opportunities.
Time-series-analysis techniques applied to nuclear-material accounting

International Nuclear Information System (INIS)

Pike, D.H.; Morrison, G.W.; Downing, D.J.

1982-05-01

This document is designed to introduce the reader to the applications of Time Series Analysis techniques to Nuclear Material Accountability data. Time series analysis techniques are designed to extract information from a collection of random variables ordered by time by seeking to identify any trends, patterns, or other structure in the series. Since nuclear material accountability data is a time series, one can extract more information using time series analysis techniques than by using other statistical techniques. Specifically, the objective of this document is to examine the applicability of time series analysis techniques to enhance loss detection of special nuclear materials. An introductory section examines the current industry approach which utilizes inventory differences. The error structure of inventory differences is presented. Time series analysis techniques discussed include the Shewhart Control Chart, the Cumulative Summation of Inventory Differences Statistics (CUSUM) and the Kalman Filter and Linear Smoother
Optical coherence tomography used for internal biometrics

Science.gov (United States)

Chang, Shoude; Sherif, Sherif; Mao, Youxin; Flueraru, Costel

2007-06-01

Traditional biometric technologies used for security and person identification essentially deal with fingerprints, hand geometry and face images. However, because all these technologies use external features of human body, they can be easily fooled and tampered with by distorting, modifying or counterfeiting these features. Nowadays, internal biometrics which detects the internal ID features of an object is becoming increasingly important. Being capable of exploring under-skin structure, optical coherence tomography (OCT) system can be used as a powerful tool for internal biometrics. We have applied fiber-optic and full-field OCT systems to detect the multiple-layer 2D images and 3D profile of the fingerprints, which eventually result in a higher discrimination than the traditional 2D recognition methods. More importantly, the OCT based fingerprint recognition has the ability to easily distinguish artificial fingerprint dummies by analyzing the extracted layered surfaces. Experiments show that our OCT systems successfully detected the dummy, which was made of plasticene and was used to bypass the commercially available fingerprint scanning system with a false accept rate (FAR) of 100%.
Clinical and epidemiological rounds. Time series

Directory of Open Access Journals (Sweden)

León-Álvarez, Alba Luz

2016-07-01

Full Text Available Analysis of time series is a technique that implicates the study of individuals or groups observed in successive moments in time. This type of analysis allows the study of potential causal relationships between different variables that change over time and relate to each other. It is the most important technique to make inferences about the future, predicting, on the basis or what has happened in the past and it is applied in different disciplines of knowledge. Here we discuss different components of time series, the analysis technique and specific examples in health research.
A Survey and Proposed Framework on the Soft Biometrics Technique for Human Identification in Intelligent Video Surveillance System

Directory of Open Access Journals (Sweden)

Min-Gu Kim

2012-01-01

Full Text Available Biometrics verification can be efficiently used for intrusion detection and intruder identification in video surveillance systems. Biometrics techniques can be largely divided into traditional and the so-called soft biometrics. Whereas traditional biometrics deals with physical characteristics such as face features, eye iris, and fingerprints, soft biometrics is concerned with such information as gender, national origin, and height. Traditional biometrics is versatile and highly accurate. But it is very difficult to get traditional biometric data from a distance and without personal cooperation. Soft biometrics, although featuring less accuracy, can be used much more freely though. Recently, many researchers have been made on human identification using soft biometrics data collected from a distance. In this paper, we use both traditional and soft biometrics for human identification and propose a framework for solving such problems as lighting, occlusion, and shadowing.
A Survey and Proposed Framework on the Soft Biometrics Technique for Human Identification in Intelligent Video Surveillance System

Science.gov (United States)

Kim, Min-Gu; Moon, Hae-Min; Chung, Yongwha; Pan, Sung Bum

2012-01-01

Biometrics verification can be efficiently used for intrusion detection and intruder identification in video surveillance systems. Biometrics techniques can be largely divided into traditional and the so-called soft biometrics. Whereas traditional biometrics deals with physical characteristics such as face features, eye iris, and fingerprints, soft biometrics is concerned with such information as gender, national origin, and height. Traditional biometrics is versatile and highly accurate. But it is very difficult to get traditional biometric data from a distance and without personal cooperation. Soft biometrics, although featuring less accuracy, can be used much more freely though. Recently, many researchers have been made on human identification using soft biometrics data collected from a distance. In this paper, we use both traditional and soft biometrics for human identification and propose a framework for solving such problems as lighting, occlusion, and shadowing. PMID:22919273
A survey and proposed framework on the soft biometrics technique for human identification in intelligent video surveillance system.

Science.gov (United States)

Kim, Min-Gu; Moon, Hae-Min; Chung, Yongwha; Pan, Sung Bum

2012-01-01

Biometrics verification can be efficiently used for intrusion detection and intruder identification in video surveillance systems. Biometrics techniques can be largely divided into traditional and the so-called soft biometrics. Whereas traditional biometrics deals with physical characteristics such as face features, eye iris, and fingerprints, soft biometrics is concerned with such information as gender, national origin, and height. Traditional biometrics is versatile and highly accurate. But it is very difficult to get traditional biometric data from a distance and without personal cooperation. Soft biometrics, although featuring less accuracy, can be used much more freely though. Recently, many researchers have been made on human identification using soft biometrics data collected from a distance. In this paper, we use both traditional and soft biometrics for human identification and propose a framework for solving such problems as lighting, occlusion, and shadowing.
The non-contact biometric identified bio signal measurement sensor and algorithms.

Science.gov (United States)

Kim, Chan-Il; Lee, Jong-Ha

2018-04-25

In these days, wearable devices have been developed for effectively measuring biological data. However, these devices have tissue allege and noise problem. To solve these problems, biometric measurement based on a non-contact method, such as face image sequencing is developed. This makes it possible to measure biometric data without any operation and side effects. However, it is impossible for a remote center to identify the person whose data are measured by the novel methods. In this paper, we propose the novel non-contact heart rate and blood pressure imaging system, Deep Health Eye. This system has authentication process at the same time as measuring bio signals, through non-contact method. In the future, this system can be convenient home bio signal monitoring system by combined with smart mirror.
Integer-valued time series

NARCIS (Netherlands)

van den Akker, R.

2007-01-01

This thesis adresses statistical problems in econometrics. The first part contributes statistical methodology for nonnegative integer-valued time series. The second part of this thesis discusses semiparametric estimation in copula models and develops semiparametric lower bounds for a large class of
Tongue prints in biometric authentication: A pilot study.

Science.gov (United States)

Jeddy, Nadeem; Radhika, T; Nithya, S

2017-01-01

Biometric authentication is an important process for the identification and verification of individuals for security purposes. There are many biometric systems that are currently in use and also being researched. Tongue print is a new biometric authentication tool that is unique and cannot be easily forged because no two tongue prints are similar. The present study aims to evaluate the common morphological features of the tongue and its variations in males and females. The usefulness of alginate impression and dental cast in obtaining the lingual impression was also evaluated. The study sample included twenty participants. The participants were subjected to visual examination following which digital photographs of the dorsal surface of the tongue were taken. Alginate impressions of the tongue were made, and casts were prepared using dental stone. The photographs and the casts were analyzed by two observers separately for the surface morphology including shape, presence or absence of fissures and its pattern of distribution. Three reference points were considered to determine the shape of the tongue. The most common morphological feature on the dorsum of the tongue was the presence of central fissures. Multiple vertical fissures were observed in males whereas single vertical fissure was a common finding in females. The fissures were predominantly shallow in males and deep in females. The tongue was predominantly U shaped in males and females. V-shaped tongue was observed in 25% of females. Tongue prints are useful in biometric authentication. The methodology used in the study is simple, easy and can be adopted by dentists on a regular basis. However, large-scale studies are required to validate the results and also identify other features of the tongue that can be used in forensics and biometric authentication process.

Robust Forecasting of Non-Stationary Time Series

NARCIS (Netherlands)

Croux, C.; Fried, R.; Gijbels, I.; Mahieu, K.

2010-01-01

This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency. The proposed method is shown to produce reliable
Enhanced ATM Security using Biometric Authentication and Wavelet Based AES

Directory of Open Access Journals (Sweden)

Sreedharan Ajish

2016-01-01

Full Text Available The traditional ATM terminal customer recognition systems rely only on bank cards, passwords and such identity verification methods are not perfect and functions are too single. Biometrics-based authentication offers several advantages over other authentication methods, there has been a significant surge in the use of biometrics for user authentication in recent years. This paper presents a highly secured ATM banking system using biometric authentication and wavelet based Advanced Encryption Standard (AES algorithm. Two levels of security are provided in this proposed design. Firstly we consider the security level at the client side by providing biometric authentication scheme along with a password of 4-digit long. Biometric authentication is achieved by considering the fingerprint image of the client. Secondly we ensure a secured communication link between the client machine to the bank server using an optimized energy efficient and wavelet based AES processor. The fingerprint image is the data for encryption process and 4-digit long password is the symmetric key for the encryption process. The performance of ATM machine depends on ultra-high-speed encryption, very low power consumption, and algorithmic integrity. To get a low power consuming and ultra-high speed encryption at the ATM machine, an optimized and wavelet based AES algorithm is proposed. In this system biometric and cryptography techniques are used together for personal identity authentication to improve the security level. The design of the wavelet based AES processor is simulated and the design of the energy efficient AES processor is simulated in Quartus-II software. Simulation results ensure its proper functionality. A comparison among other research works proves its superiority.
A novel biometric authentication approach using ECG and EMG signals.

Science.gov (United States)

Belgacem, Noureddine; Fournier, Régis; Nait-Ali, Amine; Bereksi-Reguig, Fethi

2015-05-01

Security biometrics is a secure alternative to traditional methods of identity verification of individuals, such as authentication systems based on user name and password. Recently, it has been found that the electrocardiogram (ECG) signal formed by five successive waves (P, Q, R, S and T) is unique to each individual. In fact, better than any other biometrics' measures, it delivers proof of subject's being alive as extra information which other biometrics cannot deliver. The main purpose of this work is to present a low-cost method for online acquisition and processing of ECG signals for person authentication and to study the possibility of providing additional information and retrieve personal data from an electrocardiogram signal to yield a reliable decision. This study explores the effectiveness of a novel biometric system resulting from the fusion of information and knowledge provided by ECG and EMG (Electromyogram) physiological recordings. It is shown that biometrics based on these ECG/EMG signals offers a novel way to robustly authenticate subjects. Five ECG databases (MIT-BIH, ST-T, NSR, PTB and ECG-ID) and several ECG signals collected in-house from volunteers were exploited. A palm-based ECG biometric system was developed where the signals are collected from the palm of the subject through a minimally intrusive one-lead ECG set-up. A total of 3750 ECG beats were used in this work. Feature extraction was performed on ECG signals using Fourier descriptors (spectral coefficients). Optimum-Path Forest classifier was used to calculate the degree of similarity between individuals. The obtained results from the proposed approach look promising for individuals' authentication.
Binary Biometrics: An Analytic Framework to Estimate the Bit Error Probability under Gaussian Assumption

NARCIS (Netherlands)

Kelkboom, E.J.C.; Molina, G.; Kevenaar, T.A.M.; Veldhuis, Raymond N.J.; Jonker, Willem

2008-01-01

In recent years the protection of biometric data has gained increased interest from the scientific community. Methods such as the helper data system, fuzzy extractors, fuzzy vault and cancellable biometrics have been proposed for protecting biometric data. Most of these methods use cryptographic
On the Feasibility of Interoperable Schemes in Hand Biometrics

Directory of Open Access Journals (Sweden)

Miguel A. Ferrer

2012-02-01

Full Text Available Personal recognition through hand-based biometrics has attracted the interest of many researchers in the last twenty years. A significant number of proposals based on different procedures and acquisition devices have been published in the literature. However, comparisons between devices and their interoperability have not been thoroughly studied. This paper tries to fill this gap by proposing procedures to improve the interoperability among different hand biometric schemes. The experiments were conducted on a database made up of 8,320 hand images acquired from six different hand biometric schemes, including a flat scanner, webcams at different wavelengths, high quality cameras, and contactless devices. Acquisitions on both sides of the hand were included. Our experiment includes four feature extraction methods which determine the best performance among the different scenarios for two of the most popular hand biometrics: hand shape and palm print. We propose smoothing techniques at the image and feature levels to reduce interdevice variability. Results suggest that comparative hand shape offers better performance in terms of interoperability than palm prints, but palm prints can be more effective when using similar sensors.
SU-E-T-502: Biometrically Accepted Patient Records

International Nuclear Information System (INIS)

Basavatia, A; Kalnicki, S; Garg, M; Lukaj, A; Hong, L; Fret, J; Yaparpalvi, R; Tome, W

2014-01-01

Purpose: To implement a clinically useful palm vein pattern recognition biometric system to treat the correct treatment plan to the correct patient each and every time and to check-in the patient into the department to access the correct medical record. Methods: A commercially available hand vein scanning system was paired to Aria and utilized an ADT interface from the hospital electronic health system. Integration at two points in Aria, version 11 MR2, first at the appointment tracker screen for the front desk medical record access and second at the queue screen on the 4D treatment console took place for patient daily time-out. A test patient was utilized to check accuracy of identification as well as to check that no unintended interactions take place between the 4D treatment console and the hand vein scanning system. This system has been in clinical use since December 2013. Results: Since implementation, 445 patients have been enrolled into our biometric system. 95% of patients learn the correct methodology of hand placement on the scanner in the first try. We have had two instances of patient not found because of a bad initial scan. We simply erased the scanned metric and the patient enrolled again in those cases. The accuracy of the match is 100% for each patient, we have not had one patient misidentified. We can state this because we still use patient photo and date of birth as identifiers. A QA test patient is run monthly to check the integrity of the system. Conclusion: By utilizing palm vein scans along with the date of birth and patient photo, another means of patient identification now exits. This work indicates the successful implementation of technology in the area of patient safety by closing the gap of treating the wrong plan to a patient in radiation oncology. FOJP Service Corporation covered some of the costs of the hardware and software of the palm vein pattern recognition biometric system
SU-E-T-502: Biometrically Accepted Patient Records

Energy Technology Data Exchange (ETDEWEB)

Basavatia, A; Kalnicki, S; Garg, M; Lukaj, A; Hong, L [Montefiore Medical Center, Bronx, NY (United States); Fret, J [Montefiore Information Technology, Yonkers, NY (United States); Yaparpalvi, R [Montefiore Medical Center, Bronx, NY (United States); Montefiore Medical Center, Bronx, NY (United States); Tome, W [Montefiore Medical Center/Albert Einstein College of Medicine, Bronx, NY (United States)

2014-06-01

Purpose: To implement a clinically useful palm vein pattern recognition biometric system to treat the correct treatment plan to the correct patient each and every time and to check-in the patient into the department to access the correct medical record. Methods: A commercially available hand vein scanning system was paired to Aria and utilized an ADT interface from the hospital electronic health system. Integration at two points in Aria, version 11 MR2, first at the appointment tracker screen for the front desk medical record access and second at the queue screen on the 4D treatment console took place for patient daily time-out. A test patient was utilized to check accuracy of identification as well as to check that no unintended interactions take place between the 4D treatment console and the hand vein scanning system. This system has been in clinical use since December 2013. Results: Since implementation, 445 patients have been enrolled into our biometric system. 95% of patients learn the correct methodology of hand placement on the scanner in the first try. We have had two instances of patient not found because of a bad initial scan. We simply erased the scanned metric and the patient enrolled again in those cases. The accuracy of the match is 100% for each patient, we have not had one patient misidentified. We can state this because we still use patient photo and date of birth as identifiers. A QA test patient is run monthly to check the integrity of the system. Conclusion: By utilizing palm vein scans along with the date of birth and patient photo, another means of patient identification now exits. This work indicates the successful implementation of technology in the area of patient safety by closing the gap of treating the wrong plan to a patient in radiation oncology. FOJP Service Corporation covered some of the costs of the hardware and software of the palm vein pattern recognition biometric system.
Biometrics for home networks security

KAUST Repository

Ansari, Imran Shafique; Ahmad, Qutbuddin S.

2009-01-01

Hacking crimes committed to the home networks are increasing. Advanced network protection is not always possible for the home networks. In this paper we will study the ability of using biometric systems for authentication in home networks. ©2009
Multimodal biometric method that combines veins, prints, and shape of a finger

Science.gov (United States)

Kang, Byung Jun; Park, Kang Ryoung; Yoo, Jang-Hee; Kim, Jeong Nyeo

2011-01-01

Multimodal biometrics provides high recognition accuracy and population coverage by using various biometric features. A single finger contains finger veins, fingerprints, and finger geometry features; by using multimodal biometrics, information on these multiple features can be simultaneously obtained in a short time and their fusion can outperform the use of a single feature. This paper proposes a new finger recognition method based on the score-level fusion of finger veins, fingerprints, and finger geometry features. This research is novel in the following four ways. First, the performances of the finger-vein and fingerprint recognition are improved by using a method based on a local derivative pattern. Second, the accuracy of the finger geometry recognition is greatly increased by combining a Fourier descriptor with principal component analysis. Third, a fuzzy score normalization method is introduced; its performance is better than the conventional Z-score normalization method. Fourth, finger-vein, fingerprint, and finger geometry recognitions are combined by using three support vector machines and a weighted SUM rule. Experimental results showed that the equal error rate of the proposed method was 0.254%, which was lower than those of the other methods.
Analytical template protection performance and maximum key size given a Gaussian-modeled biometric source

NARCIS (Netherlands)

Kelkboom, E.J.C.; Breebaart, Jeroen; Buhan, I.R.; Veldhuis, Raymond N.J.; Vijaya Kumar, B.V.K.; Prabhakar, Salil; Ross, Arun A.

2010-01-01

Template protection techniques are used within biometric systems in order to protect the stored biometric template against privacy and security threats. A great portion of template protection techniques are based on extracting a key from or binding a key to a biometric sample. The achieved
Characterizing time series via complexity-entropy curves

Science.gov (United States)

Ribeiro, Haroldo V.; Jauregui, Max; Zunino, Luciano; Lenzi, Ervin K.

2017-06-01

The search for patterns in time series is a very common task when dealing with complex systems. This is usually accomplished by employing a complexity measure such as entropies and fractal dimensions. However, such measures usually only capture a single aspect of the system dynamics. Here, we propose a family of complexity measures for time series based on a generalization of the complexity-entropy causality plane. By replacing the Shannon entropy by a monoparametric entropy (Tsallis q entropy) and after considering the proper generalization of the statistical complexity (q complexity), we build up a parametric curve (the q -complexity-entropy curve) that is used for characterizing and classifying time series. Based on simple exact results and numerical simulations of stochastic processes, we show that these curves can distinguish among different long-range, short-range, and oscillating correlated behaviors. Also, we verify that simulated chaotic and stochastic time series can be distinguished based on whether these curves are open or closed. We further test this technique in experimental scenarios related to chaotic laser intensity, stock price, sunspot, and geomagnetic dynamics, confirming its usefulness. Finally, we prove that these curves enhance the automatic classification of time series with long-range correlations and interbeat intervals of healthy subjects and patients with heart disease.
Study of Biometric Identification Method Based on Naked Footprint

Directory of Open Access Journals (Sweden)

Raji Rafiu King

2013-10-01

Full Text Available The scale of deployment of biometric identity-verification systems has recently seen an enormous increase owing to the need for more secure and reliable way of identifying people. Footprint identification which can be defined as the measurement of footprint features for recognizing the identity of a user has surfaced recently. This study is based on a biometric personal identification method using static footprint features viz. friction ridge / texture and foot shape / silhouette. To begin with, naked footprints of users are captured; images then undergo pre processing followed by the extraction of two features; shape using Gradient Vector Flow （GVF） snake model and minutiae extraction respectively. Matching is then effected based on these two features followed by a fusion of these two results for either a reject or accept decision. Our shape matching feature is based on cosine similarity while the texture one is based on miniature score matching. The results from our research establish that the naked footprint is a credible biometric feature as two barefoot impressions of an individual match perfectly while that of two different persons shows a great deal of dissimilarity. Normal 0 false false false IN X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Doi: 10.12777/ijse.5.2.29-35 How to cite this article: King
A Collaborative Evaluation Framework for Biometric Connected Devices in Healthcare.

Science.gov (United States)

Farnia, Troskah; Jaulent, Marie Christine; Marchand, Guillaume; Yasini, Mobin

2017-01-01

A large number of biometric connected devices are currently available with a variety of designs. Healthcare users cannot easily choose the reliable ones that correspond the best to their healthcare problems. The existing evaluation methods do not consider at the same time aspects of connectivity and healthcare usage. In this study, a collaborative evaluation framework for biometric connected devices in healthcare usage is proposed. This framework contains six dimensions: medical validity, technical reliability, usability, ergonomy, legal compliance, and accuracy of measurements. In a first step, these dimensions were assessed by designing a self administered questionnaire answered by the stakeholders (patients, health professionals, payers, and manufacturers). A case study was then carried out in a second step to test this framework in a project of telemonitoring for heart failure patients. The results are in favor of the efficiency of the proposed framework as a decision making tool in healthcare usage.
Ranking Based Locality Sensitive Hashing Enabled Cancelable Biometrics: Index-of-Max Hashing

OpenAIRE

Jin, Zhe; Lai, Yen-Lung; Hwang, Jung-Yeon; Kim, Soohyung; Teoh, Andrew Beng Jin

2017-01-01

In this paper, we propose a ranking based locality sensitive hashing inspired two-factor cancelable biometrics, dubbed "Index-of-Max" (IoM) hashing for biometric template protection. With externally generated random parameters, IoM hashing transforms a real-valued biometric feature vector into discrete index (max ranked) hashed code. We demonstrate two realizations from IoM hashing notion, namely Gaussian Random Projection based and Uniformly Random Permutation based hashing schemes. The disc...
Biometrics for home networks security

KAUST Repository

Ansari, Imran Shafique

2009-01-01

Hacking crimes committed to the home networks are increasing. Advanced network protection is not always possible for the home networks. In this paper we will study the ability of using biometric systems for authentication in home networks. ©2009 IEEE.
No age discrimination for biometrics

CSIR Research Space (South Africa)

Lessing, MM

2008-07-01

Full Text Available . The research considers biometric advancements in the areas of travel and immigration, healthcare, law enforcement and banking. For the purpose of this study, adults are considered the individuals and groups in a working environment. Many of these applications...
Direct Problems and Inverse Problems in Biometric Systems

OpenAIRE

Mihailescu Marius Iulian

2013-01-01

The article purpose is to describe the two sides of biometrics technologies, direct problems and inverse problems. The advance that we face today in field of Information Technology makes Information Security an inseparable part. The authentication has a huge role when we deal about security. The problems that can appear in implementing and developing biometrics systems is raising many problems, and one of the goal of this article is to focus on direct and inverse problems which is a new and c...
Biometric Borders and Counterterrorism

Science.gov (United States)

2010-12-01

licenses, credit cards, online retailers , and even military installations all rely on various methods to identify and authenticate individuals in... Malaysia ..................................................................................92 2. 2004—Pakistan and Belgium...first state to establish a national biometric screening program was Malaysia in 1998 with several others that followed suit in 2004–2006, many of which
Complex network approach to fractional time series

Energy Technology Data Exchange (ETDEWEB)

Manshour, Pouya [Physics Department, Persian Gulf University, Bushehr 75169 (Iran, Islamic Republic of)

2015-10-15

In order to extract correlation information inherited in stochastic time series, the visibility graph algorithm has been recently proposed, by which a time series can be mapped onto a complex network. We demonstrate that the visibility algorithm is not an appropriate one to study the correlation aspects of a time series. We then employ the horizontal visibility algorithm, as a much simpler one, to map fractional processes onto complex networks. The degree distributions are shown to have parabolic exponential forms with Hurst dependent fitting parameter. Further, we take into account other topological properties such as maximum eigenvalue of the adjacency matrix and the degree assortativity, and show that such topological quantities can also be used to predict the Hurst exponent, with an exception for anti-persistent fractional Gaussian noises. To solve this problem, we take into account the Spearman correlation coefficient between nodes' degrees and their corresponding data values in the original time series.
SecurePhone: a mobile phone with biometric authentication and e-signature support for dealing secure transactions on the fly

Science.gov (United States)

Ricci, R.; Chollet, G.; Crispino, M. V.; Jassim, S.; Koreman, J.; Olivar-Dimas, M.; Garcia-Salicetti, S.; Soria-Rodriguez, P.

2006-05-01

This article presents an overview of the SecurePhone project, with an account of the first results obtained. SecurePhone's primary aim is to realise a mobile phone prototype - the 'SecurePhone' - in which biometrical authentication enables users to deal secure, dependable transactions over a mobile network. The SecurePhone is based on a commercial PDA-phone, supplemented with specific software modules and a customised SIM card. It integrates in a single environment a number of advanced features: access to cryptographic keys through strong multimodal biometric authentication; appending and verification of digital signatures; real-time exchange and interactive modification of (esigned) documents and voice recordings. SecurePhone's 'biometric recogniser' is based on original research. A fused combination of three different biometric methods - speaker, face and handwritten signature verification - is exploited, with no need for dedicated hardware components. The adoption of non-intrusive, psychologically neutral biometric techniques is expected to mitigate rejection problems that often inhibit the social use of biometrics, and speed up the spread of e-signature technology. Successful biometric authentication grants access to SecurePhone's built-in esignature services through a user-friendly interface. Special emphasis is accorded to the definition of a trustworthy security chain model covering all aspects of system operation. The SecurePhone is expected to boost m-commerce and open new scenarios for m-business and m-work, by changing the way people interact and by improving trust and confidence in information technologies, often considered intimidating and difficult to use. Exploitation plans will also explore other application domains (physical and logical access control, securised mobile communications).

Introduction to time series analysis and forecasting

CERN Document Server

Montgomery, Douglas C; Kulahci, Murat

2008-01-01

An accessible introduction to the most current thinking in and practicality of forecasting techniques in the context of time-oriented data. Analyzing time-oriented data and forecasting are among the most important problems that analysts face across many fields, ranging from finance and economics to production operations and the natural sciences. As a result, there is a widespread need for large groups of people in a variety of fields to understand the basic concepts of time series analysis and forecasting. Introduction to Time Series Analysis and Forecasting presents the time series analysis branch of applied statistics as the underlying methodology for developing practical forecasts, and it also bridges the gap between theory and practice by equipping readers with the tools needed to analyze time-oriented data and construct useful, short- to medium-term, statistically based forecasts.
Biometric Identifiers and Border Security: 9/11 Commission Recommendations and Related Issues

National Research Council Canada - National Science Library

Morgan, Daniel; Krouse, William

2005-01-01

.... This report provides an overview of biometric technologies and the major U.S. biometric border screening systems, including US-VISIT, and discusses issues such as cost, performance, and user acceptance...
Concordance and interchangeability of biometric measurements of ocular axial length in patients awaiting cataract surgery.

Science.gov (United States)

Martín-Serrano, María José; Roman-Ortiz, Carmen; Villa-Sáez, M Luz; Labrador-Castellanos, M Purificación; Blanco-Carrasco, Rosario; Lozano-Ballesteros, Felicidad; Pedraza-Martín, Carmen; José-Herrero, M Teresa San; López-Ropero, Ana M; Tenías Burillo, José María

2014-01-01

To estimate in patients awaiting cataract surgery the concordance and interchangeability of axial eye length measurements performed with the aid of various biometric methods (optical or ultrasonic) by different operators (nurses) at different times during the period prior to surgery. We selected 182 consecutive eyes from 91 patients.Ocular axial length was measured with the aid of 2 methods (IOLMaster® and Ocuscan®) by 9 randomly allocated technicians at 2 different times during the waiting period. The concordance between measurements was evaluated by means of the intraclass correlation coefficient (ICC); the interchangeability of the results was assessed with Bland Altman plots and Passing and Bablok regression. The measurements were consistent between biometric methods (ICC 0.975, 95% confidence interval [CI] 0.968 to 0.980) and measurement dates (ICC 0.996, 95% CI 0.995 to 0.997). Interobserver agreement was more heterogeneous (ICC range 0.844 to 0.998). No systematic errors were observed among the various biometric methods and measurement dates. Because measurement of axial length in phakic patients may be technician-dependent, the technician's experience should be noted in the protocols of ophthalmology services.
Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance.

Science.gov (United States)

Liu, Yongli; Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao

2018-01-01

Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy.
Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance

Science.gov (United States)

Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao

2018-01-01

Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy. PMID:29795600
The foundations of modern time series analysis

CERN Document Server

Mills, Terence C

2011-01-01

This book develops the analysis of Time Series from its formal beginnings in the 1890s through to the publication of Box and Jenkins' watershed publication in 1970, showing how these methods laid the foundations for the modern techniques of Time Series analysis that are in use today.
Voice Biometrics for Information Assurance Applications

National Research Council Canada - National Science Library

Kang, George

2002-01-01

In 2002, the President of the United States established an organization within the DOD to develop and promulgate biometrics technologies to achieve security in information, information systems, weapons, and facilities...
Time series clustering in large data sets

Directory of Open Access Journals (Sweden)

Jiří Fejfar

2011-01-01

Full Text Available The clustering of time series is a widely researched area. There are many methods for dealing with this task. We are actually using the Self-organizing map (SOM with the unsupervised learning algorithm for clustering of time series. After the first experiment (Fejfar, Weinlichová, Šťastný, 2009 it seems that the whole concept of the clustering algorithm is correct but that we have to perform time series clustering on much larger dataset to obtain more accurate results and to find the correlation between configured parameters and results more precisely. The second requirement arose in a need for a well-defined evaluation of results. It seems useful to use sound recordings as instances of time series again. There are many recordings to use in digital libraries, many interesting features and patterns can be found in this area. We are searching for recordings with the similar development of information density in this experiment. It can be used for musical form investigation, cover songs detection and many others applications.The objective of the presented paper is to compare clustering results made with different parameters of feature vectors and the SOM itself. We are describing time series in a simplistic way evaluating standard deviations for separated parts of recordings. The resulting feature vectors are clustered with the SOM in batch training mode with different topologies varying from few neurons to large maps.There are other algorithms discussed, usable for finding similarities between time series and finally conclusions for further research are presented. We also present an overview of the related actual literature and projects.
BioTwist: overcoming severe distortions in ridge-based biometrics for successful identification

NARCIS (Netherlands)

Kotzerke, Johannes

2016-01-01

Biometrics rely on a physical trait's permanence and stability over time, as well as its individuality, robustness and ease to be captured. Challenges arise when working with newborns or infants because of the tininess and fragility of an infant's features, their uncooperative nature and their rapid
Capillary-Patterns for Biometric Authentication

NARCIS (Netherlands)

Paloma Benedicto, J.; Bruekers, A.A.M.; Presura, C.N.; Garcia Molina, G.

2007-01-01

In this report, we present a method using the capillary structuresunder the "distal interphalangeal joint" (DIP joint), which is located between the second and third (distal) phalanges of the finger, for achieving secure biometric authentication. Images of the DIPjoint are acquired using a
Transmission of linear regression patterns between time series: from relationship in time series to complex networks.

Science.gov (United States)

Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong; Ding, Yinghui

2014-07-01

The linear regression parameters between two time series can be different under different lengths of observation period. If we study the whole period by the sliding window of a short period, the change of the linear regression parameters is a process of dynamic transmission over time. We tackle fundamental research that presents a simple and efficient computational scheme: a linear regression patterns transmission algorithm, which transforms linear regression patterns into directed and weighted networks. The linear regression patterns (nodes) are defined by the combination of intervals of the linear regression parameters and the results of the significance testing under different sizes of the sliding window. The transmissions between adjacent patterns are defined as edges, and the weights of the edges are the frequency of the transmissions. The major patterns, the distance, and the medium in the process of the transmission can be captured. The statistical results of weighted out-degree and betweenness centrality are mapped on timelines, which shows the features of the distribution of the results. Many measurements in different areas that involve two related time series variables could take advantage of this algorithm to characterize the dynamic relationships between the time series from a new perspective.
Combining two strategies to optimize biometric decisions against spoofing attacks

Science.gov (United States)

Li, Weifeng; Poh, Norman; Zhou, Yicong

2014-09-01

Spoof attack by replicating biometric traits represents a real threat to an automatic biometric verification/ authentication system. This is because the system, originally designed to distinguish between genuine users from impostors, simply cannot distinguish between a replicated biometric sample (replica) from a live sample. An effective solution is to obtain some measures that can indicate whether or not a biometric trait has been tempered with, e.g., liveness detection measures. These measures are referred to as evidence of spoofing or anti-spoofing measures. In order to make the final accept/rejection decision, a straightforward solution to define two thresholds: one for the anti-spoofing measure, and another for the verification score. We compared two variants of a method that relies on applying two thresholds - one to the verification (matching) score and another to the anti-spoofing measure. Our experiments carried out using a signature database as well as by simulation show that both the brute-force and its probabilistic variant turn out to be optimal under different operating conditions.
Hand biometric recognition based on fused hand geometry and vascular patterns.

Science.gov (United States)

Park, GiTae; Kim, Soowon

2013-02-28

A hand biometric authentication method based on measurements of the user's hand geometry and vascular pattern is proposed. To acquire the hand geometry, the thickness of the side view of the hand, the K-curvature with a hand-shaped chain code, the lengths and angles of the finger valleys, and the lengths and profiles of the fingers were used, and for the vascular pattern, the direction-based vascular-pattern extraction method was used, and thus, a new multimodal biometric approach is proposed. The proposed multimodal biometric system uses only one image to extract the feature points. This system can be configured for low-cost devices. Our multimodal biometric-approach hand-geometry (the side view of the hand and the back of hand) and vascular-pattern recognition method performs at the score level. The results of our study showed that the equal error rate of the proposed system was 0.06%.
Biometrics and smart card based applications for nuclear industry

International Nuclear Information System (INIS)

Nishanth Reddy, J.; Dheeraj Reddy, J.; Narender Reddy, J.

2004-01-01

Biometrics has emerged as a convenient, foolproof and well-accepted technology for identification around the globe. Nucleonix has developed innovative solutions based on finger scan biometrics for various industries. This paper closely looks into the application areas for the nuclear industry and how it will benefit this industry, in terms of identification, access control, security of PCs and applications, attendance, machinery usage control and other custom applications. (author)
Lag space estimation in time series modelling

DEFF Research Database (Denmark)

Goutte, Cyril

1997-01-01

The purpose of this article is to investigate some techniques for finding the relevant lag-space, i.e. input information, for time series modelling. This is an important aspect of time series modelling, as it conditions the design of the model through the regressor vector a.k.a. the input layer...
Time-series prediction and applications a machine intelligence approach

CERN Document Server

Konar, Amit

2017-01-01

This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications. It also proposes new uncertainty management techniques in an economic time-series using type-2 fuzzy sets for prediction of the time-series at a given time point from its preceding value in fluctuating business environments. It employs machine learning to determine repetitively occurring similar structural patterns in the time-series and uses stochastic automaton to predict the most probabilistic structure at a given partition of the time-series. Such predictions help in determining probabilistic moves in a stock index time-series Primarily written for graduate students and researchers in computer science, the book is equally useful for researchers/professionals in business intelligence and stock index prediction. A background of undergraduate level mathematics is presumed, although not mandatory, for most of the sections. Exercises with tips are provided at...
Supporting the Maritime Information Dominance: Optimizing Tactical Network for Biometric Data Sharing in Maritime Interdiction Operations

Science.gov (United States)

2015-03-01

biometric data collection. Capture role- player mock biometric data including finger prints, iris scans, and facial recognition photos. (MOC training...MARITIME INFORMATION DOMINANCE: OPTIMIZING TACTICAL NETWORK FOR BIOMETRIC DATA SHARING IN MARITIME INTERDICTION OPERATIONS by Adam R. Sinsel...MARITIME INFORMATION DOMINANCE: OPTIMIZING TACTICAL NETWORK FOR BIOMETRIC DATA SHARING IN MARITIME INTERDICTION OPERATIONS 6. AUTHOR(S) Adam R
A Time Series Forecasting Method

Directory of Open Access Journals (Sweden)

Wang Zhao-Yu

2017-01-01

Full Text Available This paper proposes a novel time series forecasting method based on a weighted self-constructing clustering technique. The weighted self-constructing clustering processes all the data patterns incrementally. If a data pattern is not similar enough to an existing cluster, it forms a new cluster of its own. However, if a data pattern is similar enough to an existing cluster, it is removed from the cluster it currently belongs to and added to the most similar cluster. During the clustering process, weights are learned for each cluster. Given a series of time-stamped data up to time t, we divide it into a set of training patterns. By using the weighted self-constructing clustering, the training patterns are grouped into a set of clusters. To estimate the value at time t + 1, we find the k nearest neighbors of the input pattern and use these k neighbors to decide the estimation. Experimental results are shown to demonstrate the effectiveness of the proposed approach.
Reference charts for fetal biometric parameters in twin pregnancies according to chorionicity.

Science.gov (United States)

Araujo Júnior, Edward; Ruano, Rodrigo; Javadian, Pouya; Martins, Wellington P; Elito, Julio; Pires, Claudio Rodrigues; Zanforlin Filho, Sebastião Marques

2014-04-01

The objective of this article is to determine reference values for fetal biometric parameters in twin pregnancies and to compare these values between monochorionic and dichorionic pregnancies. A retrospective cross-sectional study was conducted among 157 monochorionic and 176 dichorionic twin pregnancies between 14 and 38 weeks of gestation. Biometric measurements included the biparietal diameter (BPD), abdominal circumference (AC), femurs length (FL) and estimated fetal weight (EFW). To evaluate the correlation between biometric parameters and gestational age, polynomial regression models were created, with adjustments using the coefficient of determination (R(2) ). Comparison between monochorionic and dichorionic pregnancies was performed using analysis of covariance. The mean BPD, AC, FL and EFW for the dichorionic pregnancies were 56.16 mm, 191.1 mm, 41.08 mm and 816.1 g, respectively. The mean BPD, AC, FL and EFW for the monochorionic pregnancies were 57.14 mm, 184.2 mm, 39.29 mm and 723.4 g, respectively. There was a statistical difference between mono and dichorionic pregnancies for all the biometric parameters (BPD p = 0.012; AC p = 0.047; FL p = 0.007; EFW p = 0.011). Reference curves of biometric parameters in twin pregnancies were determined. Biometric parameters were statistically different between monochorionic and dichorionic pregnancies. © 2014 John Wiley & Sons, Ltd.
Stochastic nature of series of waiting times

Science.gov (United States)

Anvari, Mehrnaz; Aghamohammadi, Cina; Dashti-Naserabadi, H.; Salehi, E.; Behjat, E.; Qorbani, M.; Khazaei Nezhad, M.; Zirak, M.; Hadjihosseini, Ali; Peinke, Joachim; Tabar, M. Reza Rahimi

2013-06-01

Although fluctuations in the waiting time series have been studied for a long time, some important issues such as its long-range memory and its stochastic features in the presence of nonstationarity have so far remained unstudied. Here we find that the “waiting times” series for a given increment level have long-range correlations with Hurst exponents belonging to the interval 1/2time distribution. We find that the logarithmic difference of waiting times series has a short-range correlation, and then we study its stochastic nature using the Markovian method and determine the corresponding Kramers-Moyal coefficients. As an example, we analyze the velocity fluctuations in high Reynolds number turbulence and determine the level dependence of Markov time scales, as well as the drift and diffusion coefficients. We show that the waiting time distributions exhibit power law tails, and we were able to model the distribution with a continuous time random walk.

A proposed simple method for measurement in the anterior chamber angle: biometric gonioscopy.

Science.gov (United States)

Congdon, N G; Spaeth, G L; Augsburger, J; Klancnik, J; Patel, K; Hunter, D G

1999-11-01

To design a system of gonioscopy that will allow greater interobserver reliability and more clearly defined screening cutoffs for angle closure than current systems while being simple to teach and technologically appropriate for use in rural Asia, where the prevalence of angle-closure glaucoma is highest. Clinic-based validation and interobserver reliability trial. Study 1: 21 patients 18 years of age and older recruited from a university-based specialty glaucoma clinic; study 2: 32 patients 18 years of age and older recruited from the same clinic. In study 1, all participants underwent conventional gonioscopy by an experienced observer (GLS) using the Spaeth system and in the same eye also underwent Scheimpflug photography, ultrasonographic measurement of anterior chamber depth and axial length, automatic refraction, and biometric gonioscopy with measurement of the distance from iris insertion to Schwalbe's line using a reticule based in the slit-lamp ocular. In study 2, all participants underwent both conventional gonioscopy and biometric gonioscopy by an experienced gonioscopist (NGC) and a medical student with no previous training in gonioscopy (JK). Study 1: The association between biometric gonioscopy and conventional gonioscopy, Scheimpflug photography, and other factors known to correlate with the configuration of the angle. Study 2: Interobserver agreement using biometric gonioscopy compared to that obtained with conventional gonioscopy. In study 1, there was an independent, monotonic, statistically significant relationship between biometric gonioscopy and both Spaeth angle (P = 0.001, t test) and Spaeth insertion (P = 0.008, t test) grades. Biometric gonioscopy correctly identified six of six patients with occludable angles according to Spaeth criteria. Biometric gonioscopic grade was also significantly associated with the anterior chamber angle as measured by Scheimpflug photography (P = 0.005, t test). In study 2, the intraclass correlation coefficient
Efficient Approximate OLAP Querying Over Time Series

DEFF Research Database (Denmark)

Perera, Kasun Baruhupolage Don Kasun Sanjeewa; Hahmann, Martin; Lehner, Wolfgang

2016-01-01

The ongoing trend for data gathering not only produces larger volumes of data, but also increases the variety of recorded data types. Out of these, especially time series, e.g. various sensor readings, have attracted attention in the domains of business intelligence and decision making. As OLAP...... queries play a major role in these domains, it is desirable to also execute them on time series data. While this is not a problem on the conceptual level, it can become a bottleneck with regards to query run-time. In general, processing OLAP queries gets more computationally intensive as the volume...... of data grows. This is a particular problem when querying time series data, which generally contains multiple measures recorded at fine time granularities. Usually, this issue is addressed either by scaling up hardware or by employing workload based query optimization techniques. However, these solutions...
A Dynamic Fuzzy Cluster Algorithm for Time Series

Directory of Open Access Journals (Sweden)

Min Ji

2013-01-01

clustering time series by introducing the definition of key point and improving FCM algorithm. The proposed algorithm works by determining those time series whose class labels are vague and further partitions them into different clusters over time. The main advantage of this approach compared with other existing algorithms is that the property of some time series belonging to different clusters over time can be partially revealed. Results from simulation-based experiments on geographical data demonstrate the excellent performance and the desired results have been obtained. The proposed algorithm can be applied to solve other clustering problems in data mining.
Likelihood-ratio-based biometric verification

NARCIS (Netherlands)

Bazen, A.M.; Veldhuis, Raymond N.J.

2002-01-01

This paper presents results on optimal similarity measures for biometric verification based on fixed-length feature vectors. First, we show that the verification of a single user is equivalent to the detection problem, which implies that for single-user verification the likelihood ratio is optimal.
Likelihood Ratio-Based Biometric Verification

NARCIS (Netherlands)

Bazen, A.M.; Veldhuis, Raymond N.J.

The paper presents results on optimal similarity measures for biometric verification based on fixed-length feature vectors. First, we show that the verification of a single user is equivalent to the detection problem, which implies that, for single-user verification, the likelihood ratio is optimal.
A novel weight determination method for time series data aggregation

Science.gov (United States)

Xu, Paiheng; Zhang, Rong; Deng, Yong

2017-09-01

Aggregation in time series is of great importance in time series smoothing, predicting and other time series analysis process, which makes it crucial to address the weights in times series correctly and reasonably. In this paper, a novel method to obtain the weights in time series is proposed, in which we adopt induced ordered weighted aggregation (IOWA) operator and visibility graph averaging (VGA) operator and linearly combine the weights separately generated by the two operator. The IOWA operator is introduced to the weight determination of time series, through which the time decay factor is taken into consideration. The VGA operator is able to generate weights with respect to the degree distribution in the visibility graph constructed from the corresponding time series, which reflects the relative importance of vertices in time series. The proposed method is applied to two practical datasets to illustrate its merits. The aggregation of Construction Cost Index (CCI) demonstrates the ability of proposed method to smooth time series, while the aggregation of The Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) illustrate how proposed method maintain the variation tendency of original data.
Machine Learning-Empowered Biometric Methods for Biomedicine Applications

Directory of Open Access Journals (Sweden)

Qingxue Zhang

2017-07-01

Full Text Available Nowadays, pervasive computing technologies are paving a promising way for advanced smart health applications. However, a key impediment faced by wide deployment of these assistive smart devices, is the increasing privacy and security issue, such as how to protect access to sensitive patient data in the health record. Focusing on this challenge, biometrics are attracting intense attention in terms of effective user identification to enable confidential health applications. In this paper, we take special interest in two bio-potential-based biometric modalities, electrocardiogram (ECG and electroencephalogram (EEG, considering that they are both unique to individuals, and more reliable than token (identity card and knowledge-based (username/password methods. After extracting effective features in multiple domains from ECG/EEG signals, several advanced machine learning algorithms are introduced to perform the user identification task, including Neural Network, K-nearest Neighbor, Bagging, Random Forest and AdaBoost. Experimental results on two public ECG and EEG datasets show that ECG is a more robust biometric modality compared to EEG, leveraging a higher signal to noise ratio and also more distinguishable morphological patterns. Among different machine learning classifiers, the random forest greatly outperforms the others and owns an identification rate as high as 98%. This study is expected to demonstrate that properly selected biometric empowered by an effective machine learner owns a great potential, to enable confidential biomedicine applications in the era of smart digital health.
Foundations of Sequence-to-Sequence Modeling for Time Series

OpenAIRE

Kuznetsov, Vitaly; Mariet, Zelda

2018-01-01

The availability of large amounts of time series data, paired with the performance of deep-learning algorithms on a broad class of problems, has recently led to significant interest in the use of sequence-to-sequence models for time series forecasting. We provide the first theoretical analysis of this time series forecasting framework. We include a comparison of sequence-to-sequence modeling to classical time series models, and as such our theory can serve as a quantitative guide for practiti...
Climate Prediction Center (CPC) Global Precipitation Time Series

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The global precipitation time series provides time series charts showing observations of daily precipitation as well as accumulated precipitation compared to normal...
Climate Prediction Center (CPC) Global Temperature Time Series

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The global temperature time series provides time series charts using station based observations of daily temperature. These charts provide information about the...
Fundamental limits for privacy-preserving biometric identification systems that support authentication

NARCIS (Netherlands)

Ignatenko, T.; Willems, F.M.J.

2015-01-01

In this paper we analyze two types of biometric identification systems with protected templates that also support authentication. In the first system two terminals observe biometric enrollment and identification sequences of a number of individuals. It is the goal of these terminals to form a common
Recurrent Neural Network Applications for Astronomical Time Series

Science.gov (United States)

Protopapas, Pavlos

2017-06-01

The benefits of good predictive models in astronomy lie in early event prediction systems and effective resource allocation. Current time series methods applicable to regular time series have not evolved to generalize for irregular time series. In this talk, I will describe two Recurrent Neural Network methods, Long Short-Term Memory (LSTM) and Echo State Networks (ESNs) for predicting irregular time series. Feature engineering along with a non-linear modeling proved to be an effective predictor. For noisy time series, the prediction is improved by training the network on error realizations using the error estimates from astronomical light curves. In addition to this, we propose a new neural network architecture to remove correlation from the residuals in order to improve prediction and compensate for the noisy data. Finally, I show how to set hyperparameters for a stable and performant solution correctly. In this work, we circumvent this obstacle by optimizing ESN hyperparameters using Bayesian optimization with Gaussian Process priors. This automates the tuning procedure, enabling users to employ the power of RNN without needing an in-depth understanding of the tuning procedure.
Hand Biometric Recognition Based on Fused Hand Geometry and Vascular Patterns

Science.gov (United States)

Park, GiTae; Kim, Soowon

2013-01-01

A hand biometric authentication method based on measurements of the user's hand geometry and vascular pattern is proposed. To acquire the hand geometry, the thickness of the side view of the hand, the K-curvature with a hand-shaped chain code, the lengths and angles of the finger valleys, and the lengths and profiles of the fingers were used, and for the vascular pattern, the direction-based vascular-pattern extraction method was used, and thus, a new multimodal biometric approach is proposed. The proposed multimodal biometric system uses only one image to extract the feature points. This system can be configured for low-cost devices. Our multimodal biometric-approach hand-geometry (the side view of the hand and the back of hand) and vascular-pattern recognition method performs at the score level. The results of our study showed that the equal error rate of the proposed system was 0.06%. PMID:23449119
Cattle identification based in biometric features of the muzzle

OpenAIRE

Monteiro, Marta; Cadavez, Vasco; Monteiro, Fernando C.

2015-01-01

Cattle identification has been a serious problem for breeding association. Muzzle pattern or nose print has the same characteristic with the human fingerprint which is the most popular biometric marker. The identification accuracy and the processing time are two key challenges of any cattle identification methodology. This paper presents a robust and fast cattle identification scheme from muzzle images using Speed-up Robust Features matching. The matching refinement technique based on the mat...
Human body as a set of biometric features identified by means of optoelectronics

Science.gov (United States)

Podbielska, Halina; Bauer, Joanna

2005-09-01

Human body posses many unique, singular features that are impossible to copy or forge. Nowadays, to establish and to ensure the public security requires specially designed devices and systems. Biometrics is a field of science and technology, exploiting human body characteristics for people recognition. It identifies the most characteristic and unique ones in order to design and construct systems capable to recognize people. In this paper some overview is given, presenting the achievements in biometrics. The verification and identification process is explained, along with the way of evaluation of biometric recognition systems. The most frequently human biometrics used in practice are shortly presented, including fingerprints, facial imaging (including thermal characteristic), hand geometry and iris patterns.
NCI: DCTD: Biometric Research Program

Science.gov (United States)

The Biometric Research Program (BRP) is the statistical and biomathematical component of the Division of Cancer Treatment, Diagnosis and Centers (DCTDC). Its members provide statistical leadership for the national and international research programs of the division in developmental therapeutics, developmental diagnostics, diagnostic imaging and clinical trials.
NCI: DCTD: Biometric Research Branch

Science.gov (United States)

The Biometric Research Branch (BRB) is the statistical and biomathematical component of the Division of Cancer Treatment, Diagnosis and Centers (DCTDC). Its members provide statistical leadership for the national and international research programs of the division in developmental therapeutics, developmental diagnostics, diagnostic imaging and clinical trials.
Transition Icons for Time-Series Visualization and Exploratory Analysis.

Science.gov (United States)

Nickerson, Paul V; Baharloo, Raheleh; Wanigatunga, Amal A; Manini, Todd M; Tighe, Patrick J; Rashidi, Parisa

2018-03-01

The modern healthcare landscape has seen the rapid emergence of techniques and devices that temporally monitor and record physiological signals. The prevalence of time-series data within the healthcare field necessitates the development of methods that can analyze the data in order to draw meaningful conclusions. Time-series behavior is notoriously difficult to intuitively understand due to its intrinsic high-dimensionality, which is compounded in the case of analyzing groups of time series collected from different patients. Our framework, which we call transition icons, renders common patterns in a visual format useful for understanding the shared behavior within groups of time series. Transition icons are adept at detecting and displaying subtle differences and similarities, e.g., between measurements taken from patients receiving different treatment strategies or stratified by demographics. We introduce various methods that collectively allow for exploratory analysis of groups of time series, while being free of distribution assumptions and including simple heuristics for parameter determination. Our technique extracts discrete transition patterns from symbolic aggregate approXimation representations, and compiles transition frequencies into a bag of patterns constructed for each group. These transition frequencies are normalized and aligned in icon form to intuitively display the underlying patterns. We demonstrate the transition icon technique for two time-series datasets-postoperative pain scores, and hip-worn accelerometer activity counts. We believe transition icons can be an important tool for researchers approaching time-series data, as they give rich and intuitive information about collective time-series behaviors.
Unconstrained and contactless hand geometry biometrics.

Science.gov (United States)

de-Santos-Sierra, Alberto; Sánchez-Ávila, Carmen; Del Pozo, Gonzalo Bailador; Guerra-Casanova, Javier

2011-01-01

This paper presents a hand biometric system for contact-less, platform-free scenarios, proposing innovative methods in feature extraction, template creation and template matching. The evaluation of the proposed method considers both the use of three contact-less publicly available hand databases, and the comparison of the performance to two competitive pattern recognition techniques existing in literature: namely support vector machines (SVM) and k-nearest neighbour (k-NN). Results highlight the fact that the proposed method outcomes existing approaches in literature in terms of computational cost, accuracy in human identification, number of extracted features and number of samples for template creation. The proposed method is a suitable solution for human identification in contact-less scenarios based on hand biometrics, providing a feasible solution to devices with limited hardware requirements like mobile devices.
Unconstrained and Contactless Hand Geometry Biometrics

Directory of Open Access Journals (Sweden)

Carmen Sánchez-Ávila

2011-10-01

Full Text Available This paper presents a hand biometric system for contact-less, platform-free scenarios, proposing innovative methods in feature extraction, template creation and template matching. The evaluation of the proposed method considers both the use of three contact-less publicly available hand databases, and the comparison of the performance to two competitive pattern recognition techniques existing in literature: namely Support Vector Machines (SVM and k-Nearest Neighbour (k-NN. Results highlight the fact that the proposed method outcomes existing approaches in literature in terms of computational cost, accuracy in human identification, number of extracted features and number of samples for template creation. The proposed method is a suitable solution for human identification in contact-less scenarios based on hand biometrics, providing a feasible solution to devices with limited hardware requirements like mobile devices.

The use of biometrics in the Personal Health Record (PHR).

Science.gov (United States)

Bonney, Wilfred

2011-01-01

The emergence of the Personal Health Record (PHR) has made individual health information more readily accessible to a wide range of users including patients, consumers, practitioners, and healthcare providers. However, increased accessibility of PHR threatens the confidentiality, privacy, and security of personalized health information. Therefore, a need for robust and reliable forms of authentication is of prime concern. The concept of biometric authentication is now highly visible to healthcare providers as a technology to prevent unauthorized access to individual health information. Implementing biometric authentication mechanisms to protect PHR facilitates access control and secure exchange of health information. In this paper, a literature review is used to explore the key benefits, technical barriers, challenges, and ethical implications for using biometric authentication in PHR.
Inference-Based Similarity Search in Randomized Montgomery Domains for Privacy-Preserving Biometric Identification.

Science.gov (United States)

Wang, Yi; Wan, Jianwu; Guo, Jun; Cheung, Yiu-Ming; C Yuen, Pong

2017-07-14

Similarity search is essential to many important applications and often involves searching at scale on high-dimensional data based on their similarity to a query. In biometric applications, recent vulnerability studies have shown that adversarial machine learning can compromise biometric recognition systems by exploiting the biometric similarity information. Existing methods for biometric privacy protection are in general based on pairwise matching of secured biometric templates and have inherent limitations in search efficiency and scalability. In this paper, we propose an inference-based framework for privacy-preserving similarity search in Hamming space. Our approach builds on an obfuscated distance measure that can conceal Hamming distance in a dynamic interval. Such a mechanism enables us to systematically design statistically reliable methods for retrieving most likely candidates without knowing the exact distance values. We further propose to apply Montgomery multiplication for generating search indexes that can withstand adversarial similarity analysis, and show that information leakage in randomized Montgomery domains can be made negligibly small. Our experiments on public biometric datasets demonstrate that the inference-based approach can achieve a search accuracy close to the best performance possible with secure computation methods, but the associated cost is reduced by orders of magnitude compared to cryptographic primitives.
Multifractal analysis of visibility graph-based Ito-related connectivity time series.

Science.gov (United States)

Czechowski, Zbigniew; Lovallo, Michele; Telesca, Luciano

2016-02-01

In this study, we investigate multifractal properties of connectivity time series resulting from the visibility graph applied to normally distributed time series generated by the Ito equations with multiplicative power-law noise. We show that multifractality of the connectivity time series (i.e., the series of numbers of links outgoing any node) increases with the exponent of the power-law noise. The multifractality of the connectivity time series could be due to the width of connectivity degree distribution that can be related to the exit time of the associated Ito time series. Furthermore, the connectivity time series are characterized by persistence, although the original Ito time series are random; this is due to the procedure of visibility graph that, connecting the values of the time series, generates persistence but destroys most of the nonlinear correlations. Moreover, the visibility graph is sensitive for detecting wide "depressions" in input time series.
Mathematical foundations of time series analysis a concise introduction

CERN Document Server

Beran, Jan

2017-01-01

This book provides a concise introduction to the mathematical foundations of time series analysis, with an emphasis on mathematical clarity. The text is reduced to the essential logical core, mostly using the symbolic language of mathematics, thus enabling readers to very quickly grasp the essential reasoning behind time series analysis. It appeals to anybody wanting to understand time series in a precise, mathematical manner. It is suitable for graduate courses in time series analysis but is equally useful as a reference work for students and researchers alike.
Time series analysis in the social sciences the fundamentals

CERN Document Server

Shin, Youseop

2017-01-01

Times Series Analysis in the Social Sciences is a practical and highly readable introduction written exclusively for students and researchers whose mathematical background is limited to basic algebra. The book focuses on fundamental elements of time series analysis that social scientists need to understand so they can employ time series analysis for their research and practice. Through step-by-step explanations and using monthly violent crime rates as case studies, this book explains univariate time series from the preliminary visual analysis through the modeling of seasonality, trends, and re
Data imputation analysis for Cosmic Rays time series

Science.gov (United States)

Fernandes, R. C.; Lucio, P. S.; Fernandez, J. H.

2017-05-01

The occurrence of missing data concerning Galactic Cosmic Rays time series (GCR) is inevitable since loss of data is due to mechanical and human failure or technical problems and different periods of operation of GCR stations. The aim of this study was to perform multiple dataset imputation in order to depict the observational dataset. The study has used the monthly time series of GCR Climax (CLMX) and Roma (ROME) from 1960 to 2004 to simulate scenarios of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80% and 90% of missing data compared to observed ROME series, with 50 replicates. Then, the CLMX station as a proxy for allocation of these scenarios was used. Three different methods for monthly dataset imputation were selected: AMÉLIA II - runs the bootstrap Expectation Maximization algorithm, MICE - runs an algorithm via Multivariate Imputation by Chained Equations and MTSDI - an Expectation Maximization algorithm-based method for imputation of missing values in multivariate normal time series. The synthetic time series compared with the observed ROME series has also been evaluated using several skill measures as such as RMSE, NRMSE, Agreement Index, R, R2, F-test and t-test. The results showed that for CLMX and ROME, the R2 and R statistics were equal to 0.98 and 0.96, respectively. It was observed that increases in the number of gaps generate loss of quality of the time series. Data imputation was more efficient with MTSDI method, with negligible errors and best skill coefficients. The results suggest a limit of about 60% of missing data for imputation, for monthly averages, no more than this. It is noteworthy that CLMX, ROME and KIEL stations present no missing data in the target period. This methodology allowed reconstructing 43 time series.
Algorithm for Compressing Time-Series Data

Science.gov (United States)

Hawkins, S. Edward, III; Darlington, Edward Hugo

2012-01-01

An algorithm based on Chebyshev polynomials effects lossy compression of time-series data or other one-dimensional data streams (e.g., spectral data) that are arranged in blocks for sequential transmission. The algorithm was developed for use in transmitting data from spacecraft scientific instruments to Earth stations. In spite of its lossy nature, the algorithm preserves the information needed for scientific analysis. The algorithm is computationally simple, yet compresses data streams by factors much greater than two. The algorithm is not restricted to spacecraft or scientific uses: it is applicable to time-series data in general. The algorithm can also be applied to general multidimensional data that have been converted to time-series data, a typical example being image data acquired by raster scanning. However, unlike most prior image-data-compression algorithms, this algorithm neither depends on nor exploits the two-dimensional spatial correlations that are generally present in images. In order to understand the essence of this compression algorithm, it is necessary to understand that the net effect of this algorithm and the associated decompression algorithm is to approximate the original stream of data as a sequence of finite series of Chebyshev polynomials. For the purpose of this algorithm, a block of data or interval of time for which a Chebyshev polynomial series is fitted to the original data is denoted a fitting interval. Chebyshev approximation has two properties that make it particularly effective for compressing serial data streams with minimal loss of scientific information: The errors associated with a Chebyshev approximation are nearly uniformly distributed over the fitting interval (this is known in the art as the "equal error property"); and the maximum deviations of the fitted Chebyshev polynomial from the original data have the smallest possible values (this is known in the art as the "min-max property").
Modeling of Volatility with Non-linear Time Series Model

OpenAIRE

Kim Song Yon; Kim Mun Chol

2013-01-01

In this paper, non-linear time series models are used to describe volatility in financial time series data. To describe volatility, two of the non-linear time series are combined into form TAR (Threshold Auto-Regressive Model) with AARCH (Asymmetric Auto-Regressive Conditional Heteroskedasticity) error term and its parameter estimation is studied.
Increasing the Robustness of Biometric Templates for Dynamic Signature Biometric Systems

OpenAIRE

Tolosana Moranchel, Rubén; Vera-Rodríguez, Rubén; Ortega-García, Javier; Fiérrez, Julián

2015-01-01

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. R. Tolosana, R. Vera-Rodriguez, J. Ortega-Garcia and J. Fierrez, "Increasing the robustness of biometric templates for dynamic...
Layered Ensemble Architecture for Time Series Forecasting.

Science.gov (United States)

Rahman, Md Mustafizur; Islam, Md Monirul; Murase, Kazuyuki; Yao, Xin

2016-01-01

Time series forecasting (TSF) has been widely used in many application areas such as science, engineering, and finance. The phenomena generating time series are usually unknown and information available for forecasting is only limited to the past values of the series. It is, therefore, necessary to use an appropriate number of past values, termed lag, for forecasting. This paper proposes a layered ensemble architecture (LEA) for TSF problems. Our LEA consists of two layers, each of which uses an ensemble of multilayer perceptron (MLP) networks. While the first ensemble layer tries to find an appropriate lag, the second ensemble layer employs the obtained lag for forecasting. Unlike most previous work on TSF, the proposed architecture considers both accuracy and diversity of the individual networks in constructing an ensemble. LEA trains different networks in the ensemble by using different training sets with an aim of maintaining diversity among the networks. However, it uses the appropriate lag and combines the best trained networks to construct the ensemble. This indicates LEAs emphasis on accuracy of the networks. The proposed architecture has been tested extensively on time series data of neural network (NN)3 and NN5 competitions. It has also been tested on several standard benchmark time series data. In terms of forecasting accuracy, our experimental results have revealed clearly that LEA is better than other ensemble and nonensemble methods.
Biometric monitor with electronics disposed on or in a neck collar

NARCIS (Netherlands)

2012-01-01

A highly portable biometric monitor is disclosed. At least one remote sensor member (12, 12') includes one or more biometric sensors (20, 22, 24, 25) configured for operative coupling with a patient. A neck collar (14, 114, 214, 314, 414) includes electronics (36, 40, 42, 44, 46, 48) for operating
A novel feature ranking algorithm for biometric recognition with PPG signals.

Science.gov (United States)

Reşit Kavsaoğlu, A; Polat, Kemal; Recep Bozkurt, M

2014-06-01

This study is intended for describing the application of the Photoplethysmography (PPG) signal and the time domain features acquired from its first and second derivatives for biometric identification. For this purpose, a sum of 40 features has been extracted and a feature-ranking algorithm is proposed. This proposed algorithm calculates the contribution of each feature to biometric recognition and collocates the features, the contribution of which is from great to small. While identifying the contribution of the features, the Euclidean distance and absolute distance formulas are used. The efficiency of the proposed algorithms is demonstrated by the results of the k-NN (k-nearest neighbor) classifier applications of the features. During application, each 15-period-PPG signal belonging to two different durations from each of the thirty healthy subjects were used with a PPG data acquisition card. The first PPG signals recorded from the subjects were evaluated as the 1st configuration; the PPG signals recorded later at a different time as the 2nd configuration and the combination of both were evaluated as the 3rd configuration. When the results were evaluated for the k-NN classifier model created along with the proposed algorithm, an identification of 90.44% for the 1st configuration, 94.44% for the 2nd configuration, and 87.22% for the 3rd configuration has successfully been attained. The obtained results showed that both the proposed algorithm and the biometric identification model based on this developed PPG signal are very promising for contactless recognizing the people with the proposed method. Copyright © 2014 Elsevier Ltd. All rights reserved.
Biometric Quantization through Detection Rate Optimized Bit Allocation

Directory of Open Access Journals (Sweden)

C. Chen

2009-01-01

Full Text Available Extracting binary strings from real-valued biometric templates is a fundamental step in many biometric template protection systems, such as fuzzy commitment, fuzzy extractor, secure sketch, and helper data systems. Previous work has been focusing on the design of optimal quantization and coding for each single feature component, yet the binary string—concatenation of all coded feature components—is not optimal. In this paper, we present a detection rate optimized bit allocation (DROBA principle, which assigns more bits to discriminative features and fewer bits to nondiscriminative features. We further propose a dynamic programming (DP approach and a greedy search (GS approach to achieve DROBA. Experiments of DROBA on the FVC2000 fingerprint database and the FRGC face database show good performances. As a universal method, DROBA is applicable to arbitrary biometric modalities, such as fingerprint texture, iris, signature, and face. DROBA will bring significant benefits not only to the template protection systems but also to the systems with fast matching requirements or constrained storage capability.
Biometric security based on ECG

NARCIS (Netherlands)

Ma, L.; Groot, de J.A.; Linnartz, J.P.M.G.

2011-01-01

Recently the electrocardiogram (ECG) has been proposed as a novel biometric. This paper aims to construct a reliable ECG verification system, in terms of privacy protection. To this end, an improved expression to estimate the capacity in the autocorrelation (AC) of the ECG is derived, which not only
Inter-observer variability in fetal biometric measurements.

Science.gov (United States)

Kilani, Rami; Aleyadeh, Wesam; Atieleh, Luay Abu; Al Suleimat, Abdul Mane; Khadra, Maysa; Hawamdeh, Hassan M

2018-02-01

To evaluate inter-observer variability and reproducibility of ultrasound measurements for fetal biometric parameters. A prospective cohort study was implemented in two tertiary care hospitals in Amman, Jordan; Prince Hamza Hospital and Albashir Hospital. 192 women with a singleton pregnancy at a gestational age of 18-36 weeks were the participants in the study. Transabdominal scans for fetal biometric parameter measurement were performed on study participants from the period of November 2014 to March 2015. Women who agreed to participate in the study were administered two ultrasound scans for head circumference, abdominal circumference and femur length. The correlation coefficient was calculated. Bland-Altman plots were used to analyze the degree of measurement agreement between observers. Limits of agreement ± 2 SD for the differences in fetal biometry measurements in proportions of the mean of the measurements were derived. Main outcome measures examine the reproducibility of fetal biometric measurements by different observers. High inter-observer inter-class correlation coefficient (ICC) was found for femur length (0.990) and abdominal circumference (0.996) where Bland-Altman plots showed high degrees of agreement. The highest degrees of agreement were noted in the measurement of abdominal circumference followed by head circumference. The lowest degree of agreement was found for femur length measurement. We used a paired-sample t-test and found that the mean difference between duplicate measurements was not significant (P > 0.05). Biometric fetal parameter measurements may be reproducible by different operators in the clinical setting with similar results. Fetal head circumference, abdominal circumference and femur length were highly reproducible. Large organized studies are needed to ensure accurate fetal measurements due to the important clinical implications of inaccurate measurements. Copyright © 2018. Published by Elsevier B.V.
Evaluation of biometric data and theire usage in authentication system

OpenAIRE

Peroutka, Tomáš

2009-01-01

The goal of this thesis is to introduce the main aspects of biometry, explain particular methods of biometric analysis and determine suitable methods for using in particular authentication system by multicriterial analysis. Our criteria for method analysis are: uniqueness, universality, public acceptability and policy consideration, resistence of fraud, accuracy, speed of comparison, template storage requirements, constancy of human biometric characters. The thesis deals with the effective us...
Individual Biometric Identification Using Multi-Cycle Electrocardiographic Waveform Patterns

Directory of Open Access Journals (Sweden)

Wonki Lee

2018-03-01

Full Text Available The electrocardiogram (ECG waveform conveys information regarding the electrical property of the heart. The patterns vary depending on the individual heart characteristics. ECG features can be potentially used for biometric recognition. This study presents a new method using the entire ECG waveform pattern for matching and demonstrates that the approach can potentially be employed for individual biometric identification. Multi-cycle ECG signals were assessed using an ECG measuring circuit, and three electrodes can be patched on the wrists or fingers for considering various measurements. For biometric identification, our-fold cross validation was used in the experiments for assessing how the results of a statistical analysis will generalize to an independent data set. Four different pattern matching algorithms, i.e., cosine similarity, cross correlation, city block distance, and Euclidean distances, were tested to compare the individual identification performances with a single channel of ECG signal (3-wire ECG. To evaluate the pattern matching for biometric identification, the ECG recordings for each subject were partitioned into training and test set. The suggested method obtained a maximum performance of 89.9% accuracy with two heartbeats of ECG signals measured on the wrist and 93.3% accuracy with three heartbeats for 55 subjects. The performance rate with ECG signals measured on the fingers improved up to 99.3% with two heartbeats and 100% with three heartbeats of signals for 20 subjects.
Individual Biometric Identification Using Multi-Cycle Electrocardiographic Waveform Patterns.

Science.gov (United States)

Lee, Wonki; Kim, Seulgee; Kim, Daeeun

2018-03-28

The electrocardiogram (ECG) waveform conveys information regarding the electrical property of the heart. The patterns vary depending on the individual heart characteristics. ECG features can be potentially used for biometric recognition. This study presents a new method using the entire ECG waveform pattern for matching and demonstrates that the approach can potentially be employed for individual biometric identification. Multi-cycle ECG signals were assessed using an ECG measuring circuit, and three electrodes can be patched on the wrists or fingers for considering various measurements. For biometric identification, our-fold cross validation was used in the experiments for assessing how the results of a statistical analysis will generalize to an independent data set. Four different pattern matching algorithms, i.e., cosine similarity, cross correlation, city block distance, and Euclidean distances, were tested to compare the individual identification performances with a single channel of ECG signal (3-wire ECG). To evaluate the pattern matching for biometric identification, the ECG recordings for each subject were partitioned into training and test set. The suggested method obtained a maximum performance of 89.9% accuracy with two heartbeats of ECG signals measured on the wrist and 93.3% accuracy with three heartbeats for 55 subjects. The performance rate with ECG signals measured on the fingers improved up to 99.3% with two heartbeats and 100% with three heartbeats of signals for 20 subjects.
Ocular biometric measurements in cataract surgery candidates in Portugal.

Science.gov (United States)

Ferreira, Tiago B; Hoffer, Kenneth J; Ribeiro, Filomena; Ribeiro, Paulo; O'Neill, João G

2017-01-01

Describe the ocular biometric parameters and their associations in a population of cataract surgery candidates. A cross-sectional study of 13,012 eyes of 6,506 patients was performed. Biometric parameters of the eyes were measured by optical low-coherence reflectometry. The axial length (AL), mean keratometry (K) and astigmatism, anterior chamber depth (ACD) (epithelium to lens), lens thickness (LT), and Corneal Diameter (CD) were evaluated. The mean age was 69 ± 10 years (44-99 years). Mean AL, Km, and ACD were 23.87 ± 1.55 mm (19.8-31.92 mm), 43.91 ± 1.71 D (40.61-51.14 D), and 3.25 ± 0.44 mm (2.04-5.28 mm), respectively. The mean LT was 4.32 ± 0.49 mm (2.73-5.77 mm) and the mean CD was 12.02 ± 0.46 mm (10.50-14.15 mm). The mean corneal astigmatism was 1.08 ± 0.84 D (0.00-7.58 D) and 43.5% of eyes had astigmatism ≥ 1.00 D. Male patients had longer AL and ACDs (p biometric values for the Portuguese population. The greatest predictor of ocular biometrics was gender. There was no significant correlation between age and AL, ACD, or Km. These results may be relevant in the evaluation of refractive error and in the calculation of intraocular lens power.
A window-based time series feature extraction method.

Science.gov (United States)

Katircioglu-Öztürk, Deniz; Güvenir, H Altay; Ravens, Ursula; Baykal, Nazife

2017-10-01

This study proposes a robust similarity score-based time series feature extraction method that is termed as Window-based Time series Feature ExtraCtion (WTC). Specifically, WTC generates domain-interpretable results and involves significantly low computational complexity thereby rendering itself useful for densely sampled and populated time series datasets. In this study, WTC is applied to a proprietary action potential (AP) time series dataset on human cardiomyocytes and three precordial leads from a publicly available electrocardiogram (ECG) dataset. This is followed by comparing WTC in terms of predictive accuracy and computational complexity with shapelet transform and fast shapelet transform (which constitutes an accelerated variant of the shapelet transform). The results indicate that WTC achieves a slightly higher classification performance with significantly lower execution time when compared to its shapelet-based alternatives. With respect to its interpretable features, WTC has a potential to enable medical experts to explore definitive common trends in novel datasets. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cancelable ECG biometrics using GLRT and performance improvement using guided filter with irreversible guide signal.

Science.gov (United States)

Kim, Hanvit; Minh Phuong Nguyen; Se Young Chun

2017-07-01

Biometrics such as ECG provides a convenient and powerful security tool to verify or identify an individual. However, one important drawback of biometrics is that it is irrevocable. In other words, biometrics cannot be re-used practically once it is compromised. Cancelable biometrics has been investigated to overcome this drawback. In this paper, we propose a cancelable ECG biometrics by deriving a generalized likelihood ratio test (GLRT) detector from a composite hypothesis testing in randomly projected domain. Since it is common to observe performance degradation for cancelable biometrics, we also propose a guided filtering (GF) with irreversible guide signal that is a non-invertibly transformed signal of ECG authentication template. We evaluated our proposed method using ECG-ID database with 89 subjects. Conventional Euclidean detector with original ECG template yielded 93.9% PD1 (detection probability at 1% FAR) while Euclidean detector with 10% compressed ECG (1/10 of the original data size) yielded 90.8% PD1. Our proposed GLRT detector with 10% compressed ECG yielded 91.4%, which is better than Euclidean with the same compressed ECG. GF with our proposed irreversible ECG template further improved the performance of our GLRT with 10% compressed ECG up to 94.3%, which is higher than Euclidean detector with original ECG. Lastly, we showed that our proposed cancelable ECG biometrics practically met cancelable biometrics criteria such as efficiency, re-usability, diversity and non-invertibility.
Identification and authentication. Common biometric methods review

OpenAIRE

Lysak, A.

2012-01-01

Major biometric methods used for identification and authentication purposes in modern computing systems are considered in the article. Basic classification, application areas and key differences are given.
Improving Speaker Recognition by Biometric Voice Deconstruction

Directory of Open Access Journals (Sweden)

Luis Miguel eMazaira-Fernández

2015-09-01

Full Text Available Person identification, especially in critical environments, has always been a subject of great interest. However, it has gained a new dimension in a world threatened by a new kind of terrorism that uses social networks (e.g. YouTube to broadcast its message. In this new scenario, classical identification methods (such fingerprints or face recognition have been forcedly replaced by alternative biometric characteristics such as voice, as sometimes this is the only feature available. Through the present paper, a new methodology to characterize speakers will be shown. This methodology is benefiting from the advances achieved during the last years in understanding and modelling voice production. The paper hypothesizes that a gender dependent characterization of speakers combined with the use of a new set of biometric parameters extracted from the components resulting from the deconstruction of the voice into its glottal source and vocal tract estimates, will enhance recognition rates when compared to classical approaches. A general description about the main hypothesis and the methodology followed to extract gender-dependent extended biometric parameters are given. Experimental validation is carried out both on a highly controlled acoustic condition database, and on a mobile phone network recorded under non-controlled acoustic conditions.
An Approach to Biometric Verification Based on Human Body Communication in Wearable Devices.

Science.gov (United States)

Li, Jingzhen; Liu, Yuhang; Nie, Zedong; Qin, Wenjian; Pang, Zengyao; Wang, Lei

2017-01-10

In this paper, an approach to biometric verification based on human body communication (HBC) is presented for wearable devices. For this purpose, the transmission gain S21 of volunteer's forearm is measured by vector network analyzer (VNA). Specifically, in order to determine the chosen frequency for biometric verification, 1800 groups of data are acquired from 10 volunteers in the frequency range 0.3 MHz to 1500 MHz, and each group includes 1601 sample data. In addition, to achieve the rapid verification, 30 groups of data for each volunteer are acquired at the chosen frequency, and each group contains only 21 sample data. Furthermore, a threshold-adaptive template matching (TATM) algorithm based on weighted Euclidean distance is proposed for rapid verification in this work. The results indicate that the chosen frequency for biometric verification is from 650 MHz to 750 MHz. The false acceptance rate (FAR) and false rejection rate (FRR) based on TATM are approximately 5.79% and 6.74%, respectively. In contrast, the FAR and FRR were 4.17% and 37.5%, 3.37% and 33.33%, and 3.80% and 34.17% using K-nearest neighbor (KNN) classification, support vector machines (SVM), and naive Bayesian method (NBM) classification, respectively. In addition, the running time of TATM is 0.019 s, whereas the running times of KNN, SVM and NBM are 0.310 s, 0.0385 s, and 0.168 s, respectively. Therefore, TATM is suggested to be appropriate for rapid verification use in wearable devices.
On the implementation of IP protection using biometrics based information hiding and firewall

Science.gov (United States)

Basu, Abhishek; Nandy, Kingshuk; Banerjee, Avishek; Giri, Supratick; Sarkar, Souvik; Sarkar, Subir Kumar

2016-02-01

System-on-chip-based design style creates a revolution in very large scale integration industry with design efficiency, operating speed and development time. To support this process, reuse and exchange of components are essential in electronic form called intellectual property (IP). This, however, increases the possibility of encroachment of IP of the design. So copyright protection of IP against piracy is the most important concern for IP vendors. The existing solutions for IP protection are still not secure enough with flexibility, cost, etc. This paper proposes an information-hiding-based solution for IP protection by embedding a biometric copyright information and firewall inside an IP in the form of a finite state machine with unique configuration. The scheme first introduces biometric signature-based copyright as ownership proof. Second, firewall interrupts the normal functionality of IP at the end of the user time period. The experimental outcomes of field-programmable-gate-array implementation illustrate the efficiency of the proposed method.
Energy-efficient key distribution using electrocardiograph biometric set for secure communications in wireless body healthcare networks.

Science.gov (United States)

Shi, Jinyang; Lam, Kwok-Yan; Gu, Ming; Li, Mingze; Chung, Siu-Leung

2011-10-01

Wireless body sensor network (WBSN) has gained significant interests as an important infrastructure for real-time biomedical healthcare systems, while the security of the sensitive health information becomes one of the main challenges. Due to the constraints of limited power, traditional cryptographic key distribution schemes are not suitable for WBSN. This paper proposes a novel energy-efficient approach, BodyKey, which can distribute the keys using the electrocardiograph biometrics. BodyKey represents the biometric features as ordered set, and deals with the biometric variations using set reconciliation. In this way, only limited necessary information needs to be communicated for key agreement, and the total energy consumption for key distribution can thus be reduced. Experiments on the PhysioBank Database show that BodyKey can perform an energy consumption rate of 0.01 mJ/bit with an equal accuracy rate of 97.28%, allowing the system to be used as an energy-efficient key distribution scheme for secure communications in WBSN.
Robust Biometric Score Fusion by Naive Likelihood Ratio via Receiver Operating Characteristics

NARCIS (Netherlands)

Tao, Q.; Veldhuis, Raymond N.J.

This paper presents a novel method of fusing multiple biometrics on the matching score level. We estimate the likelihood ratios of the fused biometric scores, via individual receiver operating characteristics (ROC) which construct the Naive Bayes classifier. Using a limited number of operation
Prewhitening of hydroclimatic time series? Implications for inferred change and variability across time scales

Science.gov (United States)

Razavi, Saman; Vogel, Richard

2018-02-01

Prewhitening, the process of eliminating or reducing short-term stochastic persistence to enable detection of deterministic change, has been extensively applied to time series analysis of a range of geophysical variables. Despite the controversy around its utility, methodologies for prewhitening time series continue to be a critical feature of a variety of analyses including: trend detection of hydroclimatic variables and reconstruction of climate and/or hydrology through proxy records such as tree rings. With a focus on the latter, this paper presents a generalized approach to exploring the impact of a wide range of stochastic structures of short- and long-term persistence on the variability of hydroclimatic time series. Through this approach, we examine the impact of prewhitening on the inferred variability of time series across time scales. We document how a focus on prewhitened, residual time series can be misleading, as it can drastically distort (or remove) the structure of variability across time scales. Through examples with actual data, we show how such loss of information in prewhitened time series of tree rings (so-called "residual chronologies") can lead to the underestimation of extreme conditions in climate and hydrology, particularly droughts, reconstructed for centuries preceding the historical period.
Machine learning techniques for gait biometric recognition using the ground reaction force

CERN Document Server

Mason, James Eric; Woungang, Isaac

2016-01-01

This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extractors, normalizers, and classifiers configurations that were never directly compared with one another in any previous GRF recognition research. Finally, a detailed theoretical overview of many existing machine learning techniques is presented, leading to a proposal of two novel data processing techniques developed specifically for the purpose of gait biometric recognition using GRF. This book · introduces novel machine-learning-based temporal normalization techniques · bridges research gaps concerning the effect of ...
Remote Biometrics for Robust Persistent Authentication

DEFF Research Database (Denmark)

Ingwar, Mads Ingerslew; Jensen, Christian D.

2014-01-01

This paper examines the problem of providing a robust non-invasive authentication service for mobile users in a smart environment. We base our work on the persistent authentication model (PAISE), which relies on available sensors to track principals from the location where they authenticate, e.......g., through a smart card based access control system, to the location where the authentication is required by a location-based service. The PAISE model is extended with remote biometrics to prevent the decay of authentication confidence when authenticated users encounter and interact with other users...... in the environment. The result is a calm approach to authentication, where mobile users are transparently authenticated towards the system, which allows the provision of location-based services. The output of the remote biometrics are fused using error-rate-based fusion to solve a common problem that occurs in score...
Sensor-fusion-based biometric identity verification

International Nuclear Information System (INIS)

Carlson, J.J.; Bouchard, A.M.; Osbourn, G.C.; Martinez, R.F.; Bartholomew, J.W.; Jordan, J.B.; Flachs, G.M.; Bao, Z.; Zhu, L.

1998-02-01

Future generation automated human biometric identification and verification will require multiple features/sensors together with internal and external information sources to achieve high performance, accuracy, and reliability in uncontrolled environments. The primary objective of the proposed research is to develop a theoretical and practical basis for identifying and verifying people using standoff biometric features that can be obtained with minimal inconvenience during the verification process. The basic problem involves selecting sensors and discovering features that provide sufficient information to reliably verify a person's identity under the uncertainties caused by measurement errors and tactics of uncooperative subjects. A system was developed for discovering hand, face, ear, and voice features and fusing them to verify the identity of people. The system obtains its robustness and reliability by fusing many coarse and easily measured features into a near minimal probability of error decision algorithm
Signatures of Depression in Non-Stationary Biometric Time Series

Directory of Open Access Journals (Sweden)

Milka Culic

2009-01-01

Full Text Available This paper is based on a discussion that was held during a special session on models of mental disorders, at the NeuroMath meeting in Stockholm, Sweden, in September 2008. At this occasion, scientists from different countries and different fields of research presented their research and discussed open questions with regard to analyses and models of mental disorders, in particular depression. The content of this paper emerged from these discussions and in the presentation we briefly link biomarkers (hormones, bio-signals (EEG and biomaps (brain-maps via EEG to depression and its treatments, via linear statistical models as well as nonlinear dynamic models. Some examples involving EEG-data are presented.
DTW-APPROACH FOR UNCORRELATED MULTIVARIATE TIME SERIES IMPUTATION

OpenAIRE

Phan , Thi-Thu-Hong; Poisson Caillault , Emilie; Bigand , André; Lefebvre , Alain

2017-01-01

International audience; Missing data are inevitable in almost domains of applied sciences. Data analysis with missing values can lead to a loss of efficiency and unreliable results, especially for large missing sub-sequence(s). Some well-known methods for multivariate time series imputation require high correlations between series or their features. In this paper , we propose an approach based on the shape-behaviour relation in low/un-correlated multivariate time series under an assumption of...
Estimating Body Related Soft Biometric Traits in Video Frames

Directory of Open Access Journals (Sweden)

Olasimbo Ayodeji Arigbabu

2014-01-01

Full Text Available Soft biometrics can be used as a prescreening filter, either by using single trait or by combining several traits to aid the performance of recognition systems in an unobtrusive way. In many practical visual surveillance scenarios, facial information becomes difficult to be effectively constructed due to several varying challenges. However, from distance the visual appearance of an object can be efficiently inferred, thereby providing the possibility of estimating body related information. This paper presents an approach for estimating body related soft biometrics; specifically we propose a new approach based on body measurement and artificial neural network for predicting body weight of subjects and incorporate the existing technique on single view metrology for height estimation in videos with low frame rate. Our evaluation on 1120 frame sets of 80 subjects from a newly compiled dataset shows that the mentioned soft biometric information of human subjects can be adequately predicted from set of frames.
Modeling and prototyping of biometric systems using dataflow programming

Science.gov (United States)

Minakova, N.; Petrov, I.

2018-01-01

The development of biometric systems is one of the labor-intensive processes. Therefore, the creation and analysis of approaches and techniques is an urgent task at present. This article presents a technique of modeling and prototyping biometric systems based on dataflow programming. The technique includes three main stages: the development of functional blocks, the creation of a dataflow graph and the generation of a prototype. A specially developed software modeling environment that implements this technique is described. As an example of the use of this technique, an example of the implementation of the iris localization subsystem is demonstrated. A variant of modification of dataflow programming is suggested to solve the problem related to the undefined order of block activation. The main advantage of the presented technique is the ability to visually display and design the model of the biometric system, the rapid creation of a working prototype and the reuse of the previously developed functional blocks.
Distinct iris gene expression profiles of primary angle closure glaucoma and primary open angle glaucoma and their interaction with ocular biometric parameters.

Science.gov (United States)

Seet, Li-Fong; Narayanaswamy, Arun; Finger, Sharon N; Htoon, Hla M; Nongpiur, Monisha E; Toh, Li Zhen; Ho, Henrietta; Perera, Shamira A; Wong, Tina T

2016-11-01

This study aimed to evaluate differences in iris gene expression profiles between primary angle closure glaucoma (PACG) and primary open angle glaucoma (POAG) and their interaction with biometric characteristics. Prospective study. Thirty-five subjects with PACG and thirty-three subjects with POAG who required trabeculectomy were enrolled at the Singapore National Eye Centre, Singapore. Iris specimens, obtained by iridectomy, were analysed by real-time polymerase chain reaction for expression of type I collagen, vascular endothelial growth factor (VEGF)-A, -B and -C, as well as VEGF receptors (VEGFRs) 1 and 2. Anterior segment optical coherence tomography (ASOCT) imaging for biometric parameters, including anterior chamber depth (ACD), anterior chamber volume (ACV) and lens vault (LV), was also performed pre-operatively. Relative mRNA levels between PACG and POAG irises, biometric measurements, discriminant analyses using genes and biometric parameters. COL1A1, VEGFB, VEGFC and VEGFR2 mRNA expression was higher in PACG compared to POAG irises. LV, ACD and ACV were significantly different between the two subgroups. Discriminant analyses based on gene expression, biometric parameters or a combination of both gene expression and biometrics (LV and ACV), correctly classified 94.1%, 85.3% and 94.1% of the original PACG and POAG cases, respectively. The discriminant function combining genes and biometrics demonstrated the highest accuracy in cross-validated classification of the two glaucoma subtypes. Distinct iris gene expression supports the pathophysiological differences that exist between PACG and POAG. Biometric parameters can combine with iris gene expression to more accurately define PACG from POAG. © 2016 The Authors. Clinical & Experimental Ophthalmology published by John Wiley & Sons Australia, Ltd on behalf of Royal Australian and New Zealand College of Ophthalmologists.
Variable Selection in Time Series Forecasting Using Random Forests

Directory of Open Access Journals (Sweden)

Hristos Tyralis

2017-10-01

Full Text Available Time series forecasting using machine learning algorithms has gained popularity recently. Random forest is a machine learning algorithm implemented in time series forecasting; however, most of its forecasting properties have remained unexplored. Here we focus on assessing the performance of random forests in one-step forecasting using two large datasets of short time series with the aim to suggest an optimal set of predictor variables. Furthermore, we compare its performance to benchmarking methods. The first dataset is composed by 16,000 simulated time series from a variety of Autoregressive Fractionally Integrated Moving Average (ARFIMA models. The second dataset consists of 135 mean annual temperature time series. The highest predictive performance of RF is observed when using a low number of recent lagged predictor variables. This outcome could be useful in relevant future applications, with the prospect to achieve higher predictive accuracy.
A Vein Map Biometric System

Directory of Open Access Journals (Sweden)

Felix Fuentes

2013-08-01

Full Text Available There is increasing demand world-wide, from government agencies and the private sector for cutting-edge biometric security technology that is difficult to breach but userfriendly at the same time. Some of the older tools, such as fingerprint, retina and iris scanning, and facial recognition software have all been found to have flaws and often viewed negatively because of many cultural and hygienic issues associated with them. Comparatively, mapping veins as a human barcode, a new technology, has many advantages over older technologies. Specifically, reproducing a three-dimensional model of a human vein system is impossible to replicate. Vein map technology is distinctive because of its state-of-the-art sensors are only able to recognize vein patterns if hemoglobin is actively flowing through the person
Benchmarking Quality-Dependent and Cost-Sensitive Score-Level Multimodal Biometric Fusion Algorithms

NARCIS (Netherlands)

N. Poh; T. Bourlai; J. Kittler; L. Allano; F. Alonso-Fernandez; O. Ambekar (Onkar); J. Baker; B. Dorizzi; O. Fatukasi; J. Fierrez; H. Ganster; J. Ortegia-Garcia; D. Maurer; A.A. Salah (Albert Ali); T. Scheidat; C. Vielhauer

2009-01-01

htmlabstractAutomatically verifying the identity of a person by means of biometrics (e.g. face and fingerprint) is an important application in our to-day activities such as accessing banking services and security control in airports. To increase the system reliability, several biometric devices are
Trend time-series modeling and forecasting with neural networks.

Science.gov (United States)

Qi, Min; Zhang, G Peter

2008-05-01

Despite its great importance, there has been no general consensus on how to model the trends in time-series data. Compared to traditional approaches, neural networks (NNs) have shown some promise in time-series forecasting. This paper investigates how to best model trend time series using NNs. Four different strategies (raw data, raw data with time index, detrending, and differencing) are used to model various trend patterns (linear, nonlinear, deterministic, stochastic, and breaking trend). We find that with NNs differencing often gives meritorious results regardless of the underlying data generating processes (DGPs). This finding is also confirmed by the real gross national product (GNP) series.

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