Relevant bibliographies by topics / Biometric systems

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Biometric systems'

Author: Grafiati
Published: 4 June 2021
Last updated: 11 September 2023

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Journal articles on the topic "Biometric systems"

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., Himanshi, Trisha Gulati, and Yasha Hasija. "Biometrics in Healthcare." INTERNATIONAL JOURNAL OF ADVANCED PRODUCTION AND INDUSTRIAL ENGINEERING 3, no. 2 (April 15, 2018): 13–17. http://dx.doi.org/10.35121/ijapie201804223.

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Biometrics is the discipline to measure physical human characteristics for the identification and authentication of an individual. Since ancient times, people have used voice, face, and other characteristics for the identification of an individual. With evolution, we take the individual characteristics like fingerprint scans, retina and iris images, etc., as inputs to the computer systems and then store or verify them with existing records. This report discusses biometrics and its recent roles found in the field of healthcare, medicine, genetics, and biotechnology. It includes the concept of biometrics, the system used for biometric recognition and its working, types of biometric systems, the different system algorithms applied, and system modules which are well illustrated with flow charts and block diagrams. Some of the health institutes in developed countries have started using biometric systems for checking patients and/or doctors. Biometry has enabled the proper organization and storage of the health records of individuals in medical institutes. Biometric authentication is also finding a distinct role in foiling medical claims fraud highlighting the advantages it. Even after processing via a very accurate biometric system, there is a chance of a false result due to some disease or injury to the body part subjected to biometry or faulty system leading to some error. There is also a possibility that the biometric system may harm our bodies. Moreover, biometric records need really tight system security to prevent any kind of misuse. Biometrics has a great potential to find a lot more uses in the field of healthcare. Many ideas are being proposed for implementation. In the future, biometrics can be used to detect potential disease and risks by using methods like adiposity measurement and Gas Discharge Visualization (GDV).
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Shopon, Md, Sanjida Nasreen Tumpa, Yajurv Bhatia, K. N. Pavan Kumar, and Marina L. Gavrilova. "Biometric Systems De-Identification: Current Advancements and Future Directions." Journal of Cybersecurity and Privacy 1, no. 3 (August 31, 2021): 470–95. http://dx.doi.org/10.3390/jcp1030024.

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Biometric de-identification is an emerging topic of research within the information security domain that integrates privacy considerations with biometric system development. A comprehensive overview of research in the context of authentication applications spanning physiological, behavioral, and social-behavioral biometric systems and their privacy considerations is discussed. Three categories of biometric de-identification are introduced, namely complete de-identification, auxiliary biometric preserving de-identification, and traditional biometric preserving de-identification. An overview of biometric de-identification in emerging domains such as sensor-based biometrics, social behavioral biometrics, psychological user profile identification, and aesthetic-based biometrics is presented. The article concludes with open questions and provides a rich avenue for subsequent explorations of biometric de-identification in the context of information privacy.
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Buciu, Ioan, and Alexandru Gacsadi. "Biometrics Systems and Technologies: A survey." International Journal of Computers Communications & Control 11, no. 3 (March 24, 2016): 315. http://dx.doi.org/10.15837/ijccc.2016.3.2556.

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In a nutshell, a biometric security system requires a user to provide some biometric features which are then verified against some stored biometric templates. Nowadays, the traditional password based authentication method tends to be replaced by advanced biometrics technologies. Biometric based authentication is becoming increasingly appealing and common for most of the human-computer interaction devices. To give only one recent example, Microsoft augmented its brand new Windows 10 OS version with the capability of supporting face recognition when the user login in. This chapter does not intend to cover a comprehensive and detailed list of biometric techniques. The chapter rather aims at briefly discussing biometric related items, including principles, definitions, biometric modalities and technologies along with their advantages, disadvantages or limitations, and biometric standards, targeting unfamiliar readers. It also mentions the attributes of a biometric system as well as attacks on biometrics. Important reference sources are pointed out so that the interested reader may gain deeper in-depth knowledge by consulting them.
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Reddy, M. V. Bramhananda, and V. Goutham. "IRIS TECHNOLOGY: A REVIEW ON IRIS BASED BIOMETRIC SYSTEMS FOR UNIQUE HUMAN IDENTIFICATION." International Journal of Research -GRANTHAALAYAH 6, no. 1 (January 31, 2018): 80–90. http://dx.doi.org/10.29121/granthaalayah.v6.i1.2018.1596.

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Biometric features are widely used in real time applications for unique human identification. Iris is one of the physiological biometric features which are regarded as highly reliable in biometric identification systems. Often iris is combined with other biometric features for robust biometric systems. It is also observed that biometrics is combined with cryptography for stronger security mechanisms. Since iris is unique for all individuals across the globe, many researchers focused on using iris or along with other biometrics for security with great precision. Multimodal biometric systems came into existence for better accuracy in human authentication. However, iris is considered to be most discriminatory of facial biometrics. Study of iris based human identification in ideal and non-cooperative environments can provide great insights which can help researchers and organizations that depend on iris-based biometric systems. The technical knowhow of iris strengths and weaknesses can be great advantage. This is more important in the wake of widespread use of smart devices which are vulnerable to attacks. This paper throws light into various iris-based biometric systems, issues with iris in the context of texture comparison, cancellable biometrics, iris in multi-model biometric systems, iris localization issues, challenging scenarios pertaining to accurate iris recognition and so on.
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Choudhury, Bismita, Patrick Then, Biju Issac, Valliappan Raman, and Manas Kumar Haldar. "A Survey on Biometrics and Cancelable Biometrics Systems." International Journal of Image and Graphics 18, no. 01 (January 2018): 1850006. http://dx.doi.org/10.1142/s0219467818500067.

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Now-a-days, biometric systems have replaced the password or token based authentication system in many fields to improve the security level. However, biometric system is also vulnerable to security threats. Unlike password based system, biometric templates cannot be replaced if lost or compromised. To deal with the issue of the compromised biometric template, template protection schemes evolved to make it possible to replace the biometric template. Cancelable biometric is such a template protection scheme that replaces a biometric template when the stored template is stolen or lost. It is a feature domain transformation where a distorted version of a biometric template is generated and matched in the transformed domain. This paper presents a review on the state-of-the-art and analysis of different existing methods of biometric based authentication system and cancelable biometric systems along with an elaborate focus on cancelable biometrics in order to show its advantages over the standard biometric systems through some generalized standards and guidelines acquired from the literature. We also proposed a highly secure method for cancelable biometrics using a non-invertible function based on Discrete Cosine Transformation (DCT) and Huffman encoding. We tested and evaluated the proposed novel method for 50 users and achieved good results.
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Mudhafer Taher Al Mossawy, Mais, and Loay E. George. "A digital signature system based on hand geometry - Survey." Wasit Journal of Computer and Mathematics Science 1, no. 1 (April 1, 2022): 1–14. http://dx.doi.org/10.31185/wjcm.vol1.iss1.18.

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In recent years large number of emerging automated applications faces the need to have recognition abilities of persons using their own self biometrics, before they can access the applications services. Nowadays, Biometric recognition is used, it can be used as automatic identification or automatic verification of persons based on their physiological or behavioral characteristics. There are no perfect biometric measurements;each biometry has its advantages and limitations. Each biometry requires specific vital identity to answer the identification or verification question. The suitability of a particular biometry for a particular application depends on many factors. Hand geometry/shape is a very simple biometric technology that uses the measurements of human hand to verify the identity of the individuals. The measurements include the distance between certain mark points, shape and width of fingers and size of palm. The biometric systems that employing hand geometry become widely used since they have high public acceptance. This article aims to survey several articles found in literature about hand based biometric system, and to compare different methods of biometric recognition that based on hand geometry.
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Rajvanshi, Saumya, Shiv Chauhan, and Savneet Kaur. "A New Wave in Biometric System: Systematic Study." CGC International Journal of Contemporary Technology and Research 4, no. 2 (August 5, 2022): 300–305. http://dx.doi.org/10.46860/cgcijctr.2022.07.31.300.

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Biometric system is a technique used to identify a person using its personal identification methods. The main concept of biometric systems is to provide confidentiality and security to the user. A number of biometric systems are introduced but some systems are widely used and are famous because of their usage and security they provide. Physiological and Behavioral biometrics are the two types of biometric systems. Biometric systems include physiological biometrics like face recognition, fingerprint recognition, iris recognition and behavioral biometrics like signature recognition and voice recognition. All these recognition systems are discussed in this research paper. Biometric systems work on three levels: Enrollment, Verification, and Identification. Enrollment is the process in which patterns are captured from the user and stored in the database. Verification means to confirm that the sample entered by the user belongs to him or not. When the user wants to access the data then the user must use his/her biometrics so that the system checks that the person who wants to access the data is the real owner of the data or not. This process is identification. All three levels are the working levels of the Biometric System. In earlier years, biometrics were used only at ground levels to provide basic security to data but now the tables have turned. It is playing a major role in providing security to our data. Biometrics are not only used in day-to-day life in phone unlocking, phone assistants, attendance systems but also used at advanced levels like in airports, border security, cloud computing etc. In this research paper, we will discuss the future scope of biometric systems and how it could even change the future.
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S. Raju, A., and V. Udayashankara. "A Survey on Unimodal, Multimodal Biometrics and Its Fusion Techniques." International Journal of Engineering & Technology 7, no. 4.36 (December 9, 2018): 689. http://dx.doi.org/10.14419/ijet.v7i4.36.24224.

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Presently, a variety of biometric modalities are applied to perform human identification or user verification. Unimodal biometric systems (UBS) is a technique which guarantees authentication information by processing distinctive characteristic sequences and these are fetched out from individuals. However, the performance of unimodal biometric systems restricted in terms of susceptibility to spoof attacks, non-universality, large intra-user variations, and noise in sensed data. The Multimodal biometric systems defeat various limitations of unimodal biometric systems as the sources of different biometrics typically compensate for the inherent limitations of one another. The objective of this article is to analyze various methods of information fusion for biometrics, and summarize, to conclude with direction on future research proficiency in a multimodal biometric system using ECG, Fingerprint and Face features. This paper is furnished as a ready reckoner for those researchers, who wish to persue their work in the area of biometrics.
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Chinyemba, Melissa K., and Jackson Phiri. "Gaps in the Management and Use of Biometric Data: A Case of Zambian Public and Private Institutions." Zambia ICT Journal 2, no. 1 (June 29, 2018): 35–43. http://dx.doi.org/10.33260/zictjournal.v2i1.49.

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The current physical and cybersecurity systems rely on traditional three-factor authentication to mitigate the threats posed by insider attacks. Key is the use of biometric information. Biometrics are a unique measurement and analysis of the unique physiological special traits such as voice, eye structure and others that can be used in the discipline of varying person identification. Biometry, which is the analysis of these biometrics is a complex process but guarantees identification and non-repudiation. If used to identify humans then several issues such as where is the biometric data stored? Who has access to it? And how does one ensure that such data satisfies the principle of availability. To achieve availability, secure transportation arises. To achieve transportation, non-repudiation, confidentiality and authentication, integrity arise. A storage and transport system is recommended to these challenges. In this paper, we explore the gaps into how public and private institution store and manage biometrics information. We benchmarked each organization again the ISO 30107 and ISO 24745. Our results show that while most companies are adopting and using biometrics systems, few have adopted the ISO biometrics standards that govern the storage and management of biometric information and hence creating security risk.
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Kulikov, A. A. "Application of biometric systems in face identification technologies." Russian Technological Journal 9, no. 3 (June 28, 2021): 7–14. http://dx.doi.org/10.32362/2500-316x-2021-9-3-7-14.

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The paper presents an analytical review of the application of biometric recognition systems in relation to facial image identification technologies. The classification of biometric systems is presented. The trends of technological progress in the field of biometrics and facial recognition capabilities are considered. It is determined that in 2020 there is a trend of transition from the use of biometric recognition technologies in traditional state security systems to the sphere of commercial and user applications. The process of «linking» encryption keys and passwords with the biometric parameters of the data subject is described. It is proposed that a biometric feature and a biometrics parameter mean a certain value that has a physical meaning that characterizes the subject itself. The possibility of using circular neighborhood and bilinear interpolation of pixel intensity values in biometrics is also presented. This will make it possible to build a local binary template. In order to solve the problem of identification of persons, it is advisable to investigate the essence of biometric systems in the technologies of identification of persons, their types, identifying the shortcomings of each of them, on the basis of which to present the directions of elimination and search for the most reliable technologies. The essence of the use of biometric systems in the technologies of identification of persons is, for example, that the user can provide the bank or other counterparty with evidence that it is he who wants to use the services on his accounts. At the same time, the demand has increased for contactless biometric solutions. These technologies are implemented in order to conduct additional biometric verification of users. This allows to minimize possible fraud or violation of the internal rules of the service, for example, the transfer of accounts of some registered users to others.
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Dissertations / Theses on the topic "Biometric systems"

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Nandakumar, Karthik. "Multibiometric systems fusion strategies and template security /." Diss., Connect to online resource - MSU authorized users, 2008.

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Thesis (Ph. D.)--Michigan State University. Dept. of Computer Science and Engineering, 2008.
Title from PDF t.p. (viewed on Mar. 30, 2009) Includes bibliographical references (p. 210-228). Also issued in print.
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Ferrara, Matteo <1979&gt. "Biometric Fingerprint Recognition Systems." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2009. http://amsdottorato.unibo.it/1234/1/TesiFinale_-_Matteo_Ferrara.pdf.

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Ferrara, Matteo <1979&gt. "Biometric Fingerprint Recognition Systems." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2009. http://amsdottorato.unibo.it/1234/.

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Fouad, Marwa. "Towards Template Security for Iris-based Biometric Systems." Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/22736.

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Personal identity refers to a set of attributes (e.g., name, social insurance number, etc.) that are associated with a person. Identity management is the process of creating, maintaining and destroying identities of individuals in a population. Biometric technologies are technologies developed to use statistical analysis of an individual’s biological or behavioral traits to determine his identity. Biometrics based authentication systems offer a reliable solution for identity management, because of their uniqueness, relative stability over time and security (among other reasons). Public acceptance of biometric systems will depend on their ability to ensure robustness, accuracy and security. Although robustness and accuracy of such systems are rapidly improving, there still remain some issues of security and balancing it with privacy. While the uniqueness of biometric traits offers a convenient and reliable means of identification, it also poses the risk of unauthorized cross-referencing among databases using the same biometric trait. There is also a high risk in case of a biometric database being compromised, since it’s not possible to revoke the biometric trait and re-issue a new one as is the case with passwords and smart keys. This unique attribute of biometric based authentication system poses a challenge that might slow down public acceptance and the use of biometrics for authentication purposes in large scale applications. In this research we investigate the vulnerabilities of biometric systems focusing on template security in iris-based biometric recognition systems. The iris has been well studied for authentication purposes and has been proven accurate in large scale applications in several airports and border crossings around the world. The most widely accepted iris recognition systems are based on Daugman’s model that creates a binary iris template. In this research we develop different systems using watermarking, bio-cryptography as well as feature transformation to achieve revocability and security of binary templates in iris based biometric authentication systems, while maintaining the performance that enables widespread application of these systems. All algorithms developed in this research are applicable on already existing biometric authentication systems and do not require redesign of these existing, well established iris-based authentication systems that use binary templates.
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Erbilek, Meryem. "Managing ageing effects in biometric systems." Thesis, University of Kent, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.596077.

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Biometric systems deal with the problem of determining or authenticating the identity of individuals based on measurements of their physiological or behavioural characteristics. However, these characteristics are likely to change with the natural ageing process (passage of time) and, as a result, developing biometric applications for long-term use becomes a particularly challenging task. Thus, increasingly, an understanding of the ageing process is becoming an important issue in terms of ensuring reliability in the face of changing data scenarios in biometric systems. In fact, both physical ageing (the effects of ageing across the whole ageing cycle on the biometric measurements used in the identification process) and template ageing (the effects of ageing across the time elapsed between enrolment and authentication) are important in a pmcticaJ context, and while these are obviously related phenomena, they are not the same thing, since template ageing also depends to some extent on the physical age of the subject within the relevant time frame. This thesis will describe a study to explore some important issues related to physical ageing issues of particular importance in biometric systems, in order to provide an improved understanding of the ageing problem which might be able to have a positive influence on the design, deployment and management of ageing issues in future biometric systems. We will explore and present quantitatively the results of a detaiJed investigation into the physical effects of ageing, will discuss the relationships between physical ageing and interrelated physical factors which have a bearing on how the impact of ageing can most effectively be investigated and understood, and will show how these factors can be manipulated in order to guide practical implementation towards achieving more reliable performance. We study two established and widely used biometric modalities, iris and signature, to provide a practical environment for experimentation and analysis.
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Svoboda, Jan. "System for Recognition of 3D Hand Geometry." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2014. http://www.nusl.cz/ntk/nusl-412913.

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V posledním desetiletí došlo ke zvýšení zájmu o užití 3D dat k biometrické identifikaci osob. Možná vůbec největší výzkum proběhl v oblasti 3D rozpoznávání podle obličeje, přičemž je v současné době dostupných vícero komerčních zařízení. V oblastni rozpoznávání podle 3D geometrie ruky byl v minulých letech proveden určitý výzkum jehož výsledkem však nebylo žádné komerční zařízení. Nezávisle na tomto výzkumu se v posledních letech velmi rozšířil trh s cenově dostupnými 3D sensory, což potenciálně umožňuje jejich nasazení v mnoha typech biometrických systémů. Hlavním cílem této práce je vytvořit funkční vzorek bezdotykového systému pro rozpoznávání osob podle 3D geometrie ruky, který bude používat novou levnou kameru RealSense 3D vyvíjenou v současné době firmou Intel. Jedním z problémů při použití RealSense kamery je její velmi malý form factor, který je příčinou nižší kvality výsledných snímků v porovnání s velmi drahými alternativami, které byly použity v již dříve zmíněném výzkumu 3D biometrických systémů. Práce se snaží analyzovat robustnost různých 2D a 3D příznaků a vyzkoušet několik různých přístupů k jejich fúzi. Rovněž je vyhodnocena výkonnost výsledného systému, kde je ukázáno, že navržené řešení dosahuje výsledků porovnatelných se state-of-the-art.
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Betschart, Willie. "Applying intelligent statistical methods on biometric systems." Thesis, Blekinge Tekniska Högskola, Avdelningen för signalbehandling, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-1694.

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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 layer is influenced by the general procedure of biometrics in a multimodal behavioural way. It is working in an unsupervised way and performs in an unsupervised manner. While biometric systems are increasingly adopted the technologies have some inherent problems such as false match and false non-match. In practice, a rejected user can not be interpreted as an impostor since the user simply might have problems using his/her biometric feature. The proposed methods in this project are dealing with these problems when analysing biometric usage in runtime. Another fact which may give rise to false rejections is template aging; a phenomenon where the enrolled user’s template is too old compared towards the user’s current biometric feature. A theoretical approach of template aging was known; however since the analysis of template aging detection was correlated with potential system flaws such as device defects or human generated risks such as impostor attacks this task would become difficult to solve in an unsupervised system but when ignoring the definition of template aging, the detection of similar effects was possible. One of the objectives of this project was to detect template aging in a predictive sense; this task failed to be carried out because the absence of basis performing this kind of tasks. The developed program performs abnormality detection at each incoming event from a biometric system. Each verification attempt is assumed to be from a genuine user unless any deviation according to the user's history is found, an abnormality. The possibility of an impostor attack depends on the degree of the abnormality. The application makes relative decisions between fraud possibilities or if genuine user was the source of what caused the deviations. This is presented as an alarm with the degree of impostor possibility. This intelligent layer has increased Optimum preCon´s capacity as a surveillance tool for biometrics. This product is an efficient complement to biometric systems in a steady up-going worldwide market.
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John, George Jacqueline. "Optimising multimodal fusion for biometric identification systems." Thesis, University of Kent, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.418551.

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Hitchcock, David C. "Evaluation and combination of biometric authentication systems." [Gainesville, Fla.] : University of Florida, 2003. http://purl.fcla.edu/fcla/etd/UFE0002662.

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MOMIN, ZAHID AKHTAR SHABBEER AHMAD. "Security of multimodal biometric systems against spoof attacks." Doctoral thesis, Università degli Studi di Cagliari, 2012. http://hdl.handle.net/11584/266071.

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A biometric system is essentially a pattern recognition system being used in ad-versarial environment. Since, biometric system like any conventional security system is exposed to malicious adversaries, who can manipulate data to make the system ineffective by compromising its integrity. Current theory and de- sign methods of biometric systems do not take into account the vulnerability to such adversary attacks. Therefore, evaluation of classical design methods is an open problem to investigate whether they lead to design secure systems. In order to make biometric systems secure it is necessary to understand and evalu-ate the threats and to thus develop effective countermeasures and robust system designs, both technical and procedural, if necessary. Accordingly, the extension of theory and design methods of biometric systems is mandatory to safeguard the security and reliability of biometric systems in adversarial environments. In this thesis, we provide some contributions towards this direction. Among all the potential attacks discussed in the literature, spoof attacks are one of the main threats against the security of biometric systems for identity recognition. Multimodal biometric systems are commonly believed to be in-trinsically more robust to spoof attacks than systems based on a single biomet-ric trait, as they combine information coming from different biometric traits. However, recent works have question such belief and shown that multimodal systems can be misled by an attacker (impostor) even by spoofing only one of the biometric traits. Therefore, we first provide a detailed review of state-of-the-art works in multimodal biometric systems against spoof attacks. The scope ofstate-of-the-art results is very limited, since they were obtained under a very restrictive “worst-case” hypothesis, where the attacker is assumed to be able to fabricate a perfect replica of a biometric trait whose matching score distribu-tion is identical to the one of genuine traits. Thus, we argue and investigate the validity of “worst-case” hypothesis using large set of real spoof attacks and provide empirical evidence that “worst-case” scenario can not be representa- ixtive of real spoof attacks: its suitability may depend on the specific biometric trait, the matching algorithm, and the techniques used to counterfeit the spoofed traits. Then, we propose a security evaluation methodology of biometric systems against spoof attacks that can be used in real applications, as it does not require fabricating fake biometric traits, it allows the designer to take into account the different possible qualities of fake traits used by different attackers, and it exploits only information on genuine and impostor samples which is col- lected for the training of a biometric system. Our methodology evaluates the performances under a simulated spoof attack using model of the fake score distribution that takes into account explicitly different degrees of the quality of fake biometric traits. In particular, we propose two models of the match score distribution of fake traits that take into account all different factors which can affect the match score distribution of fake traits like the particular spoofed biometric, the sensor, the algorithm for matching score computation, the technique used to construct fake biometrics, and the skills of the attacker. All these factors are summarized in a single parameter, that we call “attack strength”. Further, we propose extension of our security evaluation method to rank several biometric score fusion rules according to their relative robustness against spoof attacks. This method allows the designer to choose the most robust rule according to the method prediction. We then present empirical analysis, using data sets of face and fingerprints including real spoofed traits, to show that our proposed models provide a good approximation of fake traits’ score distribution and our method thus providing an adequate estimation of the security1 of biometric systems against spoof attacks. We also use our method to show how to evaluate the security of different multimodal systems on publicly available benchmark data sets without spoof attacks. Our experimental results show that robustness of multimodal biometric systems to spoof attacks strongly depends on the particular matching algorithm, the score fusion rule, and the attack strength of fake traits. We eventually present evidence, considering a multimodal system based on face and fingerprint biometrics, that the proposed methodology to rank score fusion rules is capable of providing correct ranking of score fusion rules under spoof attacks.
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Books on the topic "Biometric systems"

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Wayman, James, Anil Jain, Davide Maltoni, and Dario Maio, eds. Biometric Systems. London: Springer London, 2005. http://dx.doi.org/10.1007/b138151.

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Gupta, Rashmi, and Manju Khari. Multimodal Biometric Systems. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003138068.

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Rattani, Ajita, Fabio Roli, and Eric Granger, eds. Adaptive Biometric Systems. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24865-3.

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Vacca, John R. Biometric technologies and verification systems. Amsterdam: Butterworth-Heinemann/Elsevier, 2007.

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Liu, Chengjun, and Vijay Kumar Mago. Cross Disciplinary Biometric Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28457-1.

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Liu, Chengjun. Cross Disciplinary Biometric Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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James, Wayman, ed. Biometric systems: Technology, design and performance evaluation. London: Springer, 2005.

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Bodade, Rajesh M. Iris analysis for biometric recognition systems. New York: Springer, 2014.

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Obaidat, Mohammad S., Issa Traore, and Isaac Woungang, eds. Biometric-Based Physical and Cybersecurity Systems. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-98734-7.

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Bodade, Rajesh M., and Sanjay N. Talbar. Iris Analysis for Biometric Recognition Systems. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1853-1.

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Book chapters on the topic "Biometric systems"

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Genovese, Angelo, Vincenzo Piuri, and Fabio Scotti. "Biometric Systems." In Advances in Information Security, 7–32. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10365-5_2.

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Martin, Alvin, Mark Przybocki, and Joseph P. Campbell. "The NIST speaker recognition evaluation program." In Biometric Systems, 241–62. London: Springer London, 2005. http://dx.doi.org/10.1007/1-84628-064-8_8.

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Ashbourn, Julian. "Biometric Systems Defined." In Guide to Biometrics for Large-Scale Systems, 31–37. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-467-8_3.

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Richiardi, Jonas, and Krzysztof Kryszczuk. "Biometric Systems Evaluation." In Encyclopedia of Cryptography and Security, 117–24. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4419-5906-5_729.

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De Marsico, Maria. "Biometric Systems Evaluation." In Encyclopedia of Cryptography, Security and Privacy, 1–6. Berlin, Heidelberg: Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-642-27739-9_1605-1.

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Shukla, Anupam, Ritu Tiwari, and Rahul Kala. "Multimodal Biometric Systems." In Towards Hybrid and Adaptive Computing, 401–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14344-1_18.

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Zhu, Wei-Jian, Chuan-Zhi Zhuang, Jing-Wei Liu, and Ming Huang. "Design of Multimodal Biometric Information Management System Based on Commercial Systems." In Biometric Recognition, 198–205. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-97909-0_21.

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Ding, Sophia, Emilia Nunes, Pascal Bettendorff, and Weyde Lin. "Biometrics." In Trends in Data Protection and Encryption Technologies, 121–28. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-33386-6_22.

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AbstractIn biometrics, physiological characteristics (e.g., fingerprints, facial features, voices) are measured to identify individuals. Since biometry does not share the same characteristics as other authentication techniques, such as passwords or PIN codes, it is widely used as a second-factor authentication. A fully integrated solution offers significant advantages as it aligns biometric hardware, key generation, validation, and storage with the cryptographic provider, providing a coherent control environment. As a result, designing and implementing secure biometric authentication methods requires highly specialized technical expertise and experience. In addition, as biometrics become prevalent and their integration with artificial intelligence systems increases, ethical and regulatory questions become more pressing.
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Zhang, He, Jing Liu, Zhiguo Zeng, Qianli Zhou, Shengguang Li, Xingguang Li, and Hui Zhang. "Hybrid Fusion Framework for Iris Recognition Systems." In Biometric Recognition, 468–75. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-97909-0_50.

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Jain, Anil K., Sarat C. Dass, and Karthik Nandakumar. "Soft Biometric Traits for Personal Recognition Systems." In Biometric Authentication, 731–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_99.

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Conference papers on the topic "Biometric systems"

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Talabi, A. A., O. B. Longe, A. A. Muhammad, and K. Olusanya. "Cybersecurity Risk Management in Identity Systems using Biometric-based Multimodal Authentication." In 28th iSTEAMS Multidisciplinary Research Conference AIUWA The Gambia. Society for Multidisciplinary and Advanced Research Techniques - Creative Research Publishers, 2021. http://dx.doi.org/10.22624/aims/isteams-2021/v28n2p5.

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This increasing inter-connectivity of systems and dependence on computer and internet-based networks has made Cybersecurity related risks management issues major considerations in designing, developing and managing identity systems. Thus, this paper investigates Cybersecurity and related risk management challenges in Identity Management Systems by undertaking a comparative analysis of different biometric traits. The analysis proved that biometric-based multimodal systems are more secure than uni-modal systems with high accuracy rates. Also, it produced minimal false acceptance and false rejection rates. The biometric-based multi-modal authentication systems will assist organizations to restrict access to authorized users and protect digital assets by ensuring confidentiality, integrity and availability. Keywords: Cybersecurity, Risk, Identity, Biometrics, Multimodal, Behavioural, Fusion
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Chudobova, Michaela, Jan Kubicek, Radomir Scurek, and Marek Hutter. "IMPLEMENTATION OF INTELLIGENT BIOMETRIC SYSTEM FOR FACE DETECTION AND CLASSIFICATION." In 22nd SGEM International Multidisciplinary Scientific GeoConference 2022. STEF92 Technology, 2022. http://dx.doi.org/10.5593/sgem2022/2.1/s07.06.

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This article deals with the design and implementation of an intelligent biometric system that allows the detection and classification of a person's face from static image data and creates a system for evaluating its reliability. In its introductory part, it theoretically describes applied biometrics and biometric systems for security identification and user verification, and also deals with the theory of the description of algorithms for human face detection and recognition. Subsequently, the authors use the MATLAB programming language, which is highly optimized for modern processors and memory architectures, to focus on the implementation and testing of a biometric system using Viola-Jones algorithms and a convolutional neural network with a pre-trained network NetNet. Convolutional neural networks (CNN) are the most recognized and popular deep-learning neural networks, which are based on layers that perform two-dimensional (2D) convolution of input data with learned filters. In the final part there is a discussion where, based on the results of testing, the robustness and efficiency of the proposed intelligent biometric system is objectively evaluated. The results allow for the continued development of other pre-trained artificial neural networks, variable implementations for facial recognition, but also other things, such as the recognition of potentially dangerous people.
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Gilady, Erez, Dale Lindskog, and Shaun Aghili. "Intent Biometrics: An Enhanced Form of Multimodal Biometric Systems." In 2014 28th International Conference on Advanced Information Networking and Applications Workshops (WAINA). IEEE, 2014. http://dx.doi.org/10.1109/waina.2014.133.

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Taouche, Cherif, Mohamed C. Batouche, Mohamed Berkane, and Abdelmalik Taleb-Ahmed. "Multimodal biometric systems." In 2014 International Conference on Multimedia Computing and Systems (ICMCS). IEEE, 2014. http://dx.doi.org/10.1109/icmcs.2014.6911308.

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Yanushkevich, S. N. "Synthetic Biometrics for Training Users of Biometric and Biomedical Systems." In 2011 International Conference on Cyberworlds (CW). IEEE, 2011. http://dx.doi.org/10.1109/cw.2011.47.

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Wouters, Niels, Ryan Kelly, Eduardo Velloso, Katrin Wolf, Hasan Shahid Ferdous, Joshua Newn, Zaher Joukhadar, and Frank Vetere. "Biometric Mirror." In DIS '19: Designing Interactive Systems Conference 2019. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3322276.3322304.

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Sarangaraja, A. P., D. Rajagopalan, A. Vignesh, and P. Mohamed Fathimal. "Secret Sharing Scheme with Fingerprint Authentication." In International Research Conference on IOT, Cloud and Data Science. Switzerland: Trans Tech Publications Ltd, 2023. http://dx.doi.org/10.4028/p-u6em0l.

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Medical imaging is very important in medical diagnosis. X-rays, ultrasound images, CT scans, brain pictures, and patient mri images are examples of images that contain sensitive information. However, poor communication channels and loopholes in hospital and medical centre storage systems risk accessing these images by unauthorised individuals who utilise them for nefarious purposes other than diagnostics. Image encryption is a common strategy for enhancing the integrity of communication and storage channels for protecting medical images from unauthorized access. This task proposes a biometrics-based method of secret sharing. Instead of sharing secrets between participants as in encryption, the biometric properties of participants create a single biometric configuration. If the biometric vaults are verified for the required number of actual during the authentication process, participants must provide a valid encryption key from the configuration is disclosed.
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Kvarnbrink, Per, Karin Fahlquist, and Thomas Mejtoft. "Biometric interaction." In CHI '13 Extended Abstracts on Human Factors in Computing Systems. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2468356.2468772.

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Chitroub, Salim, Abdallah Meraoumia, L. Laimeche, and H. Bendjenna. "Enhancing Security of Biometric Systems Using Deep Features of Hand Biometrics." In 2019 International Conference on Computer and Information Sciences (ICCIS). IEEE, 2019. http://dx.doi.org/10.1109/iccisci.2019.8716425.

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Mishra, Prince, Vishwas Modanwal, Harkeerat Kaur, and Gaurav Varshney. "Pseudo-Biometric Identity Framework: Achieving Self-Sovereignity for Biometrics on Blockchain." In 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2021. http://dx.doi.org/10.1109/smc52423.2021.9659136.

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Reports on the topic "Biometric systems"

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Wilson, C. L., and R. M. McCabe. Simple test procedure for image-based biometric verification systems. Gaithersburg, MD: National Institute of Standards and Technology, 1999. http://dx.doi.org/10.6028/nist.ir.6336.

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Lee, Y., J. J. Filliben, R. J. Michaels, and P. J. Phillips. Sensitivity Analysis for Biometric Systems: A Methodology Based on Orthogonal Experiment Designs. National Institute of Standards and Technology, May 2012. http://dx.doi.org/10.6028/nist.ir.7855.

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Varastehpour, Soheil, Hamid Sharifzadeh, Iman Ardekani, and Abdolhossein Sarrafzadeh. Human Biometric Traits: A Systematic Review Focusing on Vascular Patterns. Unitec ePress, December 2020. http://dx.doi.org/10.34074/ocds.086.

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Authentication methods based on human traits, including fingerprint, face, iris, and palm print, have developed significantly, and currently they are mature enough to be reliably considered for human identification purposes. Recently, as a new research area, a few methods based on non-facial skin features such as vein patterns have been developed. This literature review paper explores some key biometric systems such as face recognition, iris recognition, fingerprint, and palm print, and discusses their respective advantages and disadvantages; then by providing a comprehensive analysis of these traits, and their applications, vein pattern recognition is reviewed.
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Newton, Elaine, Gerry Coleman, and Patrice Yuh. Information systems-data format for the interchange of fingerprint, facial, & other biometric information- part 2 :. Gaithersburg, MD: National Institute of Standards and Technology, 2008. http://dx.doi.org/10.6028/nist.sp.500-275.

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Koskelo, Markku, Steven Kadner, and Steven Horowitz. Biometric Access Control System Industrialization. Office of Scientific and Technical Information (OSTI), May 2020. http://dx.doi.org/10.2172/1763279.

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Faith, Becky, and Tony Roberts. Managing the Risk and Benefits of Digital Technologies in Social Assistance Provision. Institute of Development Studies (IDS), February 2022. http://dx.doi.org/10.19088/basic.2022.025.

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Aid agencies, governments, and donors are expanding investment in the digitisation of their beneficiary identification and registration systems, in digitised systems for cash payments, and in the remote and algorithmic control of humanitarian and social protection programmes. This is happening in ways that may facilitate the move from humanitarian assistance to government provision and may enable the delivery of shock-responsive social protection. Yet humanitarian and social protection actors are increasingly concerned about a range of risks and accountability vacuums associated with the adoption of these technologies. While claims for the benefits of digitisation often rest on cost savings, data relating to these costs and benefits are not easily accessible. There is also an urgent need to adopt approaches to value for money in this sector that recognise the digital dignity of beneficiaries. A knowledge gap exists around how the movement towards biometric identification and algorithmic management using humanitarian and social protection data will affect the interests of vulnerable populations – so too does a gap in research that is focused on the standpoints, interests, and priorities of these populations.
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Kulhandjian, Hovannes. Detecting Driver Drowsiness with Multi-Sensor Data Fusion Combined with Machine Learning. Mineta Transportation Institute, September 2021. http://dx.doi.org/10.31979/mti.2021.2015.

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In this research work, we develop a drowsy driver detection system through the application of visual and radar sensors combined with machine learning. The system concept was derived from the desire to achieve a high level of driver safety through the prevention of potentially fatal accidents involving drowsy drivers. According to the National Highway Traffic Safety Administration, drowsy driving resulted in 50,000 injuries across 91,000 police-reported accidents, and a death toll of nearly 800 in 2017. The objective of this research work is to provide a working prototype of Advanced Driver Assistance Systems that can be installed in present-day vehicles. By integrating two modes of visual surveillance to examine a biometric expression of drowsiness, a camera and a micro-Doppler radar sensor, our system offers high reliability over 95% in the accuracy of its drowsy driver detection capabilities. The camera is used to monitor the driver’s eyes, mouth and head movement and recognize when a discrepancy occurs in the driver's blinking pattern, yawning incidence, and/or head drop, thereby signaling that the driver may be experiencing fatigue or drowsiness. The micro-Doppler sensor allows the driver's head movement to be captured both during the day and at night. Through data fusion and deep learning, the ability to quickly analyze and classify a driver's behavior under various conditions such as lighting, pose-variation, and facial expression in a real-time monitoring system is achieved.
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Тарасова, Олена Юріївна, and Ірина Сергіївна Мінтій. Web application for facial wrinkle recognition. Кривий Ріг, КДПУ, 2022. http://dx.doi.org/10.31812/123456789/7012.

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Facial recognition technology is named one of the main trends of recent years. It’s wide range of applications, such as access control, biometrics, video surveillance and many other interactive humanmachine systems. Facial landmarks can be described as key characteristics of the human face. Commonly found landmarks are, for example, eyes, nose or mouth corners. Analyzing these key points is useful for a variety of computer vision use cases, including biometrics, face tracking, or emotion detection. Different methods produce different facial landmarks. Some methods use only basic facial landmarks, while others bring out more detail. We use 68 facial markup, which is a common format for many datasets. Cloud computing creates all the necessary conditions for the successful implementation of even the most complex tasks. We created a web application using the Django framework, Python language, OpenCv and Dlib libraries to recognize faces in the image. The purpose of our work is to create a software system for face recognition in the photo and identify wrinkles on the face. The algorithm for determining the presence and location of various types of wrinkles and determining their geometric determination on the face is programmed.
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