Journal articles on the topic 'Biometric identification systems'
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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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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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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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., 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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de Luis-Garcı́a, Rodrigo, Carlos Alberola-López, Otman Aghzout, and Juan Ruiz-Alzola. "Biometric identification systems." Signal Processing 83, no. 12 (December 2003): 2539–57. http://dx.doi.org/10.1016/j.sigpro.2003.08.001.
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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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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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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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Kuznetsov, Denis. "Identification of a Personality." MATEC Web of Conferences 155 (2018): 01018. http://dx.doi.org/10.1051/matecconf/201815501018.
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Biometric technologies are based on biometrics, measurement of the unique characteristics of a certain person. These are the unique signs received by a person from birth and acquired characteristics that can change under the influence of time or external environment. This article discusses the principles of operation, types of biometric identification systems, describes examples and areas of their application.
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Omar, Bayan. "Fusion Method with Mean-discrete Algorithm in Feature level for Identical twins Identification." UHD Journal of Science and Technology 4, no. 2 (December 27, 2020): 141. http://dx.doi.org/10.21928/uhdjst.v4n2y2020.pp141-150.
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The study on twins is an important form of study in the forensic and biometrics field as twins share similar genetic traits. A biometric is one of the common types of pattern recognition which acquires biometric data from a person. From these data, a feature is established and extracted where these features can be used to identify individual. Exiting works in biometric identification concentrate on unimodal biometric identification. The high similarity in a pair of twin’s biometric may lead to miss performance. Hence, due to their great accurateness, multimodal biometric systems have become more favored than unimodal biometric systems in identical twins identification. However, these systems are highly complex. We proposed Mean-Discrete feature based fusion algorithm for Kurdish handwriting and fingerprint for identical twins detection. Its viability and advantage over the unimodal biometric systems are highlighted. This paper employed 800 images from 50 pairs of identical twins from Kurdistan Region to carry out the experiment.
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Yin, Jing Hai, Zheng Dong Mu, and Jian Feng Hu. "Design of Identification System Based on BCI." Applied Mechanics and Materials 496-500 (January 2014): 1975–78. http://dx.doi.org/10.4028/www.scientific.net/amm.496-500.1975.
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Nowadays EEG-based identification biometric research becomes a new topic. Due to the current biometric technology are still exist some problems, therefore, an urgent needed is to find a new biometric technology. In this paper, we use EEG signals as biometrics, which is home to a new biometric research trends, cutting-edge and exploratory nature, there is a good prospect. We establish a set of EEG-based identification systems and medium-sized EEG signatures, explore effective methods of analysis biometric technology to make up for past deficiencies, to further improve and develop the theory of biometric technologies and applications for EEG-based identification technology promotion foundation.
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Smith, Jack. "Biometric identification systems update." Computer Fraud & Security Bulletin 1993, no. 4 (April 1993): 6–8. http://dx.doi.org/10.1016/0142-0496(93)90289-9.
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Medjahed, Chahreddine, Abdellatif Rahmoun, Christophe Charrier, and Freha Mezzoudj. "A deep learning-based multimodal biometric system using score fusion." IAES International Journal of Artificial Intelligence (IJ-AI) 11, no. 1 (March 1, 2022): 65. http://dx.doi.org/10.11591/ijai.v11.i1.pp65-80.
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Recent trends in artificial intelligence tools-based biometrics have overwhelming attention to security matters. The hybrid approaches are motivated by the fact that they combine mutual strengths and they overcome their limitations. Such approaches are being applied to the fields of biomedical engineering. A biometric system uses behavioural or physiological characteristics to identify an individual. The fusion of two or more of these biometric unique characteristics contributes to improving the security and overcomes the drawbacks of unimodal biometric-based security systems. This work proposes efficent multimodal biometric systems based on matching score concatenation fusion of face, left and right palm prints. Multimodal biometric identification systems using convolutional neural networks (CNN) and k-nearest neighbors (KNN) are proposed and trained to recognize and identify individuals using multi-modal biometrics scores. Some popular biometrics benchmarks such as FEI face dataset and IITD palm print database are used as raw data to train the biometric systems to design a strong and secure verification/identification system. Experiments are performed on noisy datasets to evaluate the performance of the proposed model in extreme scenarios. Computer simulation results show that the CNN and KNN multi-modal biometric system outperforms most of the most popular up to date biometric verification techniques.
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Lutsenko, K., and K. Nikulin. "VOICE SPEAKER IDENTIFICATION AS ONE OF THE CURRENT BIOMETRIC METHODS OF IDENTIFICATION OF A PERSON." Theory and Practice of Forensic Science and Criminalistics 19, no. 1 (April 2, 2020): 239–55. http://dx.doi.org/10.32353/khrife.1.2019.18.
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The article deals with the most widespread biometric identification systems of individuals, including voice recognition of the speaker on video and sound recordings. The urgency of the topic of identification of a person is due to the active informatization of modern society and the increase of flows of confidential information.
The branches of the use of biometric technologies and their general characteristics are given. Here is an overview of the use of identification groups that characterize the voice. Also in the article the division of voice identification systems into the corresponding classes is given.
The main advantages of voice biometrics such as simplicity of system realization are considered; low cost (the lowest among all biometric methods); No need for contact, the voice biometry allows for long-range verification, unlike other biometric technologies.
The analysis of existing methods of speech recognition recognition identifying a person by a combination of unique voice characteristics, determining their weak and strong points, on the basis of which the choice of the most appropriate method for solving the problem of text-independent recognition, Namely the model of Gaussian mixtures, was carried out.
The prerequisite for the development of speech technologies is a significant increase in computing capabilities, memory capacity with a significant reduction in the size of computer systems. It should also be Noted the development of mathematical methods that make it possible to perform the Necessary processing of an audio signal by isolating informative features from it.
It has been established that the development of information technologies, and the set of practical applications, which use voice recognition technologies, make this area relevant for further theoretical and practical research.
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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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Nídlová, Veronika, and Jan Hart. "Reliability of Identification Based on Fingerprints in Dual Biometric Identification Systems." Applied Mechanics and Materials 752-753 (April 2015): 1040–44. http://dx.doi.org/10.4028/www.scientific.net/amm.752-753.1040.
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At present, the development of biometrics is a widely discussed topic. This research discusses the reliability of the most used category - identification using fingerprints. There are many of these types of systems. The most affordable, and therefore the most common alternative is one that identifies users using an optical sensor. Testing was conducted on two scanners only for fingerprints, and on two systems that recognize users via their fingerprints and also through a facial image. The conclusions from the measurements were that reliability was mainly affected by the characteristics of the scanners, in particular whether the scanner identifies only based on the fingerprint, or in combination with another biometric method. Due to the fact that with combined systems manufacturers focus only on one identification circuit – usually the most modern - and not the potentially safest, i.e. a fingerprint, the results show that it is much easier to sabotage dual biometric identification devices than those that identify solely on the basis of a fingerprint. Reliability values greatly exceed the values specified by the manufacturer. The measurements show that there is a need to continuously improve dual biometric identification systems.
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Jain, Rubal, and Chander Kant. "Attacks on Biometric Systems: An Overview." International Journal of Advances in Scientific Research 1, no. 7 (September 3, 2015): 283. http://dx.doi.org/10.7439/ijasr.v1i7.1975.
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Biometrics is a pattern recognition system that refers to the use of different physiological (face, fingerprints, etc.) and behavioral (voice, gait etc.) traits for identification and verification purposes. A biometrics-based personal authentication system has numerous advantages over traditional systems such as token-based (e.g., ID cards) or knowledge-based (e.g., password) but they are at the risk of attacks. This paper presents a literature review of attack system architecture and makes progress towards various attack points in biometric system. These attacks may compromise the template resulting in reducing the security of the system and motivates to study existing biometric template protection techniques to resist these attacks.
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Dong, Xingbo, Soohyong Kim, Zhe Jin, Jung Yeon Hwang, Sangrae Cho, and Andrew Beng Jin Teoh. "Secure Chaff-less Fuzzy Vault for Face Identification Systems." ACM Transactions on Multimedia Computing, Communications, and Applications 17, no. 3 (July 22, 2021): 1–22. http://dx.doi.org/10.1145/3442198.
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Biometric cryptosystems such as fuzzy vaults represent one of the most popular approaches for secret and biometric template protection. However, they are solely designed for biometric verification, where the user is required to input both identity credentials and biometrics. Several practical questions related to the implementation of biometric cryptosystems remain open, especially in regard to biometric template protection. In this article, we propose a face cryptosystem for identification (FCI) in which only biometric input is needed. Our FCI is composed of a one-to-N search subsystem for template protection and a one-to-one match chaff-less fuzzy vault (CFV) subsystem for secret protection. The first subsystem stores N facial features, which are protected by index-of-maximum (IoM) hashing, enhanced by a fusion module for search accuracy. When a face image of the user is presented, the subsystem returns the top k matching scores and activates the corresponding vaults in the CFV subsystem. Then, one-to-one matching is applied to the k vaults based on the probe face, and the identifier or secret associated with the user is retrieved from the correct matched vault. We demonstrate that coupling between the IoM hashing and the CFV resolves several practical issues related to fuzzy vault schemes. The FCI system is evaluated on three large-scale public unconstrained face datasets (LFW, VGG2, and IJB-C) in terms of its accuracy, computation cost, template protection criteria, and security.
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B.R., Rohini, and Thippeswamy G. "BIOMETRICS-A PRELIMINARY APPROACH." International Journal of Research -GRANTHAALAYAH 5, no. 4RACSIT (April 30, 2017): 47–52. http://dx.doi.org/10.29121/granthaalayah.v5.i4racsit.2017.3350.
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Authentication plays a vital role in Information security. The need for identification of legitimate user has increased in the waking concerns for global security. Biometric recognition Systems is a major tool for Authentication mechanism. Biometrics is the ability to identify and authenticate an individual using one or more of their behavioral or physical characteristics. The Study of Different Biometric Modalities gives a better understanding of Biometric Techniques. We focus our Study on Face Biometrics. This paper emphasizes on better understanding of introduction to Biometrics, Biometric Modalities and Face recognition Techniques.
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Rai, Ankush, and Jagadeesh Kannan R. "SURVEY OF SOFT BIOMETRIC TECHNIQUES FOR GENDER IDENTIFICATION." Asian Journal of Pharmaceutical and Clinical Research 10, no. 13 (April 1, 2017): 296. http://dx.doi.org/10.22159/ajpcr.2017.v10s1.19741.
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Biometrics checks can be productively utilized for localization of intrusion in access control systems by utilizing soft computing frameworks.Biometrics procedures can be to a great extent separated into conventional and soft biometrics. The study presents a survey of the available softtechniques and comparison for gender identification from biometric techniques.
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Mróz-Gorgoń, Barbara, Wojciech Wodo, Anna Andrych, Katarzyna Caban-Piaskowska, and Cyprian Kozyra. "Biometrics Innovation and Payment Sector Perception." Sustainability 14, no. 15 (August 1, 2022): 9424. http://dx.doi.org/10.3390/su14159424.
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This paper presents an analysis of innovations in the biometrics market, which have started to play a very important role in personal identification and identification systems. The aim of the study was to analyze current customs and opinions regarding payment methods, as well as to identify threats and opportunities for new biometric solutions in this area. First, the history of the biometrics market is presented. Acceptance patterns of new technologies are explored and modified. The authors used literature reviews, qualitative research (focus groups), and quantitative research (questionnaire survey) as methods. The main value and importance of biometrics is the uniqueness of biometric patterns (e.g., face, fingerprint, iris, etc.), which takes the security of these systems to a new level. The results of the quantitative study based on the qualitative survey show positive verification of the hypothesized reasons; e.g., importantly, that the age of potential users of biometric payments influences the fear about personal data. Fear of losing personal data affects the perceived safety of biometric payments. Perceived security has a very strong influence on attitudes towards biometric payments, which is the strongest predictor of behavioral intention to use biometric payments.
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Mashagba, Eman Fares Al. "Human Identification Based on Geometric Feature Extraction Using a Number of Biometric Systems Available: Review." Computer and Information Science 9, no. 2 (May 2, 2016): 140. http://dx.doi.org/10.5539/cis.v9n2p140.
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<span style="font-size: 10.5pt; font-family: 'Times New Roman','serif'; mso-ansi-language: EN-US; mso-bidi-font-size: 12.0pt; mso-fareast-font-family: 宋体; mso-font-kerning: 1.0pt; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">Biometric technology has attracted much attention in biometric recognition. Significant online and offline applications satisfy security and human identification based on this technology. Biometric technology identifies a human based on unique features possessed by a person. Biometric features may be physiological or behavioral. A physiological feature is based on the direct measurement of a part of the human body such as a fingerprint, face, iris, blood vessel pattern at the back of the eye, vascular patterns, DNA, and hand or palm scan recognition. A behavioral feature is based on data derived from an action performed by the user. Thus, this feature measures the characteristics of the human body such as signature/handwriting, gait, voice, gesture, and keystroke dynamics. A biometric system is performed as follows: acquisition, comparison, feature extraction, and matching. The most important step is feature extraction, which determines the performance of human identification. Different methods are used for extraction, namely, appearance- and geometry-based methods. This paper reports on a review of human identification based on geometric feature extraction using several biometric systems available. We compared the different biometrics in biometric technology based on the geometric features extracted in different studies. Several biometric approaches have more geometric features, such as hand, gait, face, fingerprint, and signature features, compared with other biometric technology. Thus, geometry-based method with different biometrics can be applied simply and efficiently. The eye region extracted from the face is mainly used in face recognition. In addition, the extracted eye region has more details as the iris features.</span>
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Елена Юрьевна, Фролова, and Кошлыкова Юлия Александровна. "HUMAN IDENTIFICATION BASED ON BIOMETRIC DATA: A REVIEW OF MODERN TECHNOLOGIES." NORTH CAUCASUS LEGAL VESTNIK 1, no. 3 (September 2022): 167–74. http://dx.doi.org/10.22394/2074-7306-2022-1-3-167-174.
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Biometric identification systems have now become quite widespread, since they use not specialized physical media for recognition, but signs or features of the person himself, which makes it possible to reliably identify a person for a given purpose. Biometric identification is the process of comparing and determining the similarity between a person's data and his biometric "template". Biometrics allows you to identify and verify a person based on a set of specific and unique traits inherent in him from birth. This article discusses certain types of biometric data to be identified, problems and prospects of their application.
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Chiou, Shin-Yan. "Secure Method for Biometric-Based Recognition with Integrated Cryptographic Functions." BioMed Research International 2013 (2013): 1–12. http://dx.doi.org/10.1155/2013/623815.
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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.
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Tot, Ivan, Jovan Bajčetić, Boriša Jovanović, Mladen Trikoš, Dušan Bogićević, and Tamara Gajić. "Biometric standards and methods." Vojnotehnicki glasnik 69, no. 4 (2021): 963–77. http://dx.doi.org/10.5937/vojtehg69-32296.
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Introduction/purpose: Nowadays, user identification systems play a very important role in modern society. Complex security requirements have led experts to explore ways in which biometric data can be used to identify user identities. This paper presents an overview of biometric standards and methods which can be used to identify users in biometric systems, and therefore to protect information and communication systems. Methods: This paper deals with the problem of standardization in the field of biometrics. The first part of the paper presents concrete examples of the most widely used biometric standards. The second part of the paper gives an overview of the most used biometric methods. Results: The obtained results show that the development of biometric systems and biometric sensors contributes to better protection of identity from misuse, because biometric technologies have great potential for improving the security and accuracy of system operation. Biometric systems improve the security of users and also provide much greater precision in establishing identity. Conclusion: The development of biometric standards should focus on their interconnectivity, as well as on increasing connectivity with other IT standards.
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Gladkikh, A. A., A. K. Volkov, and T. G. Ulasyuk. "Development of biometric systems for passenger identification based on noise-resistant coding means." Civil Aviation High Technologies 24, no. 2 (April 25, 2021): 93–104. http://dx.doi.org/10.26467/2079-0619-2021-24-2-93-104.
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The paper deals with the issues of using the biometric technologies to establish identity of a passenger. The purpose of the article is to analyze the techniques of enhancing reliability of various biometric identification facilities by means of using error correction codes. The basic elements and the principle of the classical biometric system functioning are presented. On the basis of the International Civil Aviation Organization (ICAO) recommendations, the procedure features of pattern recognition are presented. The versions to adopt the biometric passenger authentication procedures are under consideration. The conclusion is drawn that with the centralized biometric databases the issues of confidentiality and information security exist. The problems are characterized by the possibility of biometric images compromise, which can potentially lead to the loss of their confidentiality and the impossibility of their further usage for personal identification. The passenger authentication procedure involving the simultaneous use of biometric parameters and contact-free SMART cards seems more reliable. SMART cards are used for distributed storage of biometric and other additional data, thus neutralizing the disadvantages of access to the centralized databases. It is shown that the subsequent step in the development of this domain is the application of biometric cryptography proposing "linking" encryption keys and passwords with the biometric parameters of the subject. Consideration is given to the principle of "fuzzy extractor" operation as one of the variants for the "biometrics-code" converter. Feasibility and necessity of upgrading the means of noise-resistant coding in the systems being studied are shown. The use of permutation decoding data algorithms capable of adequately corresponding to the particular problems of biometric identification is proposed. On the basis of the results of optical communication channels statistical modeling, the necessary and sufficient conditions for application of the permutation decoding tools for binary codes are determined. The problem to minimize memory amount for the permutation decoder cognitive map due to the permutation orbits allocation and usage of the generated loops combinations as pointers of reference plane is solved. The resulting algorithm for finding a unique orbit number and its corresponding reference plane by means of receiver formation of arbitrary parameters permutation from the set of permissible permutations is proposed.
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Aftab, Anum, Farrukh Aslam Khan, Muhammad Khurram Khan, Haider Abbas, Waseem Iqbal, and Farhan Riaz. "Hand-based multibiometric systems: state-of-the-art and future challenges." PeerJ Computer Science 7 (October 7, 2021): e707. http://dx.doi.org/10.7717/peerj-cs.707.
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The traditional methods used for the identification of individuals such as personal identification numbers (PINs), identification tags, etc., are vulnerable as they are easily compromised by the hackers. In this paper, we aim to focus on the existing multibiometric systems that use hand based modalities for the identification of individuals. We cover the existing multibiometric systems in the context of various feature extraction schemes, along with an analysis of their performance using one of the performance measures used for biometric systems. Later, we cover the literature on template protection including various cancelable biometrics and biometric cryptosystems and provide a brief comment about the methods used for multibiometric template protection. Finally, we discuss various open issues and challenges faced by researchers and propose some future directions that can enhance the security of multibiometric templates.
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Booysens, Aimee, and Serestina Viriri. "Exploration of Ear Biometrics Using EfficientNet." Computational Intelligence and Neuroscience 2022 (August 31, 2022): 1–14. http://dx.doi.org/10.1155/2022/3514807.
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Biometrics is the recognition of a human using biometric characteristics for identification, which may be physiological or behavioral. The physiological biometric features are the face, ear, iris, fingerprint, and handprint; behavioral biometrics are signatures, voice, gait pattern, and keystrokes. Numerous systems have been developed to distinguish biometric traits used in multiple applications, such as forensic investigations and security systems. With the current worldwide pandemic, facial identification has failed due to users wearing masks; however, the human ear has proven more suitable as it is visible. Therefore, the main contribution is to present the results of a CNN developed using EfficientNet. This paper presents the performance achieved in this research and shows the efficiency of EfficientNet on ear recognition. The nine variants of EfficientNets were fine-tuned and implemented on multiple publicly available ear datasets. The experiments showed that EfficientNet variant B8 achieved the best accuracy of 98.45%.
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UDROIU, Adriana-Meda, and Ștefan-Antonio DAN-ȘUTEU. "USABLE SECURITY IN BIOMETRIC AUTHENTICATION SYSTEMS." STRATEGIES XXI - Command and Staff College 17, no. 1 (July 22, 2021): 287–92. http://dx.doi.org/10.53477/2668-2028-21-37.
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Abstract: We introduce the term usable security to refer to security systems, models, mechanisms and applications that have as the main goal usability. Secure systems cannot exist without secure authentication methods. Thus we outline biometric authentication methods and we focus on iris recognition because is the most reliable and accurate method for human identification]. The most important advantage of iris biometric over other biometrics is that irises have enormous pattern variability meaning that the variation between individual is almost maximum and variation for any person across time or conditions is minimum. Taking into consideration this observations, this survey covers researches in this field, methods of technical implementation and the usability of this method as an authentication system on iOS environment.
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Pathak, Mrunal. "Multimodal Biometric Authentication for Smartphones." International Journal for Research in Applied Science and Engineering Technology 9, no. 12 (December 31, 2021): 1559–68. http://dx.doi.org/10.22214/ijraset.2021.39569.
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Abstract: Smartphones have become a crucial way of storing sensitive information; therefore, the user's privacy needs to be highly secured. This can be accomplished by employing the most reliable and accurate biometric identification system available currently which is, Eye recognition. However, the unimodal eye biometric system is not able to qualify the level of acceptability, speed, and reliability needed. There are other limitations such as constrained authentication in real time applications due to noise in sensed data, spoof attacks, data quality, lack of distinctiveness, restricted amount of freedom, lack of universality and other factors. Therefore, multimodal biometric systems have come into existence in order to increase security as well as to achieve better performance.[1] This paper provides an overview of different multimodal biometric (multibiometric) systems for smartphones being employed till now and also proposes a multimodal biometric system which can possibly overcome the limitations of the current biometric systems. Keywords: Biometrics, Unimodal, Multimodal, Fusion, Multibiometric Systems
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El Beqqal, Mohamed, Mostafa Azizi, and Jean Louis Lanet. "Multimodal access control system combining RFID, fingerprint and facial recognition." Indonesian Journal of Electrical Engineering and Computer Science 20, no. 1 (October 1, 2020): 405. http://dx.doi.org/10.11591/ijeecs.v20.i1.pp405-413.
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<span>Monomodal biometry does not constitute an effective measure to meet the desired performance requirements for large-scale applications, due to limita-tions such as noisy data, restricted degree of freedom and unacceptable error rates. Some of these problems can be solved through multimodal biometric systems that involve using a combination of two or more biometric modali-ties in a single identification system. Identification based on multiple biomet-rics represents an emerging trend. The reason for combining different modal-ities is to improve the recognition rate. In practice, multi-biometric aims to reduce the False Acceptance Ratio (FAR) and False Rejection Ratio (FRR) which are two standard metrics widely used in the accuracy of biometric sys-tems. In this paper, we will examine the different possible scenario in multi-modal biometric systems using RFID, fingerprint and facial recognition, that can be adopted to merge information and improve the overall accuracy of the system.</span>
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Rukhiran, Meennapa, Sorapak Pukdesree, and Paniti Netinant. "Biometric Cloud Services for Web-Based Examinations." International Journal of Information Technology and Web Engineering 17, no. 1 (January 2022): 1–25. http://dx.doi.org/10.4018/ijitwe.299022.
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Biometric recognition may be used in conjunction with human authentication on a smartphone to improve accuracy, reliability, and simplicity, and to aid in fraud prevention and user authentication. While single biometric authentication addresses environmental degradation and sensor noise limitations, and the single point of failure scenario in biometric systems can result in more robust biometric systems, multimodal biometric authentication can improve the accuracy of identification and recognition. The purpose of this research is to propose a facial and speech authentication system that is cloud-based and supports a web-based examination approach. The system enables students' biometrics to be registered, students to be recognized, and student recognition results to be reported. The confusion matrix is used to compare the results of positive and negative detection in various ways, including accuracy score, precision value, and recall value. Adaptive multimodal biometric authentication should be designed and evaluated for further research using the optimal weights for each biometric.
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Singh, Law Kumar, Munish Khanna, and Hitendra Garg. "Multimodal Biometric Based on Fusion of Ridge Features with Minutiae Features and Face Features." International Journal of Information System Modeling and Design 11, no. 1 (January 2020): 37–57. http://dx.doi.org/10.4018/ijismd.2020010103.
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Multimodal biometrics refers to the exploiting combination of two or more biometric modalities in an identification of a system. Fingerprint, face, retina, iris, hand geometry, DNA, and palm print are physiological traits while voice, signature, keystrokes, gait are behavioural traits used for identification by a system. Single biometric features like faces, fingerprints, irises, retinas, etc., deteriorate or change with time, environment, user mode, physiological defects, and circumstance therefore integrating multi features of biometric traits increase robustness of the system. The proposed multimodal biometrics system presents recognition based on face detection and fingerprint physiological traits. This proposed system increases the efficiency, accuracy and decreases execution time of the system as compared to the existing systems. The performance of proposed method is reported in terms of parameters such as False Rejection Rate (FRR), False Acceptance Rate (FAR) and Equal Error Rate (EER) and accuracy is reported at 95.389%.
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Zhang, Yunxia, Xin Li, Changming Zhao, Wenyin Zheng, Manqing Wang, Yongqing Zhang, Hongjiang Ma, and Dongrui Gao. "Affective EEG-Based Person Identification Using Channel Attention Convolutional Neural Dense Connection Network." Security and Communication Networks 2021 (November 22, 2021): 1–10. http://dx.doi.org/10.1155/2021/7568460.
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In the biometric recognition mode, the use of electroencephalogram (EEG) for biometric recognition has many advantages such as anticounterfeiting and nonsteal ability. Compared with traditional biometrics, EEG biometric recognition is safer and more concealed. Generally, EEG-based biometric recognition is to perform person identification (PI) through EEG signals collected by performing motor imagination and visual evoked tasks. The aim of this paper is to improve the performance of different affective EEG-based PI using a channel attention mechanism of convolutional neural dense connection network (CADCNN net) approach. Channel attention mechanism (CA) is used to handle the channel information from the EEG, while convolutional neural dense connection network (DCNN net) extracts the unique biological characteristics information for PI. The proposed method is evaluated on the state-of-the-art affective data set HEADIT. The results indicate that CADCNN net can perform PI from different affective states and reach up to 95%-96% mean correct recognition rate. This significantly outperformed a random forest (RF) and multilayer perceptron (MLP). We compared our method with the state-of-the-art EEG classifiers and models of EEG biometrics. The results show that the further extraction of the feature matrix is more robust than the direct use of the feature matrix. Moreover, the CADCNN net can effectively and efficiently capture discriminative traits, thus generalizing better over diverse human states.
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Heynen, Robert. "Biometric Aesthetics." Public 30, no. 60 (March 1, 2020): 108–25. http://dx.doi.org/10.1386/public_00009_7.
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This article examines contemporary biometric science against the backdrop of its development in nineteenth century eugenic and biostatistical practices, most notably the composite photography of Francis Galton. Focusing on automated face recognition, the article argues that contemorary biometric science is inextricable from its aesthetic investments, which in turn shape the ways in which faces and bodies are differentiated in identification systems. Based on a close reading of biometric engineering texts and projects, this aesthetico-scientific approach offers new ways of conceptualizing how biometrics constitutes rather than merely reflects bodies, and encodes racist, misogynist, and other social logics into the conception and design of technologies themselves. These are not biases that can be corrected, as ostensibly progressive biometric projects like IBM’s Diversity in Faces initiative suggest, but rather are inextricable from the biometric desire to render faces and bodies as transparent and machine-readable.
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Jansen, Fieke, Javier Sánchez-Monedero, and Lina Dencik. "Biometric identity systems in law enforcement and the politics of (voice) recognition: The case of SiiP." Big Data & Society 8, no. 2 (July 2021): 205395172110636. http://dx.doi.org/10.1177/20539517211063604.
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Biometric identity systems are now a prominent feature of contemporary law enforcement, including in Europe. Often advanced on the premise of efficiency and accuracy, they have also been the subject of significant controversy. Much attention has focussed on longer-standing biometric data collection, such as finger-printing and facial recognition, foregrounding concerns with the impact such technologies can have on the nature of policing and fundamental human rights. Less researched is the growing use of voice recognition in law enforcement. This paper examines the case of the recent Speaker Identification Integrated Project, a European wide initiative to create the first international and interoperable database of voice biometrics, now the third largest biometric database at Interpol. Drawing on Freedom of Information requests, interviews and public documentation, we outline the emergence and features of SiiP and explore how voice is recognised and attributed meaning. We understand Speaker Identification Integrated Project as constituting a particular ‘regime of recognition’ premised on the use of soft biometrics (age, language, accent and gender) to disembed voice in order to optimise for difference. This, in turn, has implications for the nature and scope of law enforcement, people's position in society, and justice concerns more broadly.
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Rajasingh, J. Paul, and D. Sai Yaswanth. "Fingerprint Authentication." International Journal of Engineering and Advanced Technology 10, no. 5 (June 30, 2021): 87–89. http://dx.doi.org/10.35940/ijeat.e2651.0610521.
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Biometrics refers to the automatic identification of a living person based on physiological or behavioural characteristics for authentication purpose. Among the existing biometric technologies are the face recognisation, fingerprint recognition, finger-geometry, hand geometry, iris recognition, vein recognition, voice recognition and signature recognition, Biometric method requires the physical presence of the person to be identified. This emphasizes its preference over the traditional method of identifying what you have such as, the use of password, a smartcard etc. Also, it potentially prevents unauthorized admittance to access control systems or fraudulent use of ATMs, Time Attendance Systems, cellular phones, smart cards, desktop PCs, Workstations, vehicles and computer networks. Biometric recognition systems offer greater security and convenience than traditional methods of personal recognition.
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Guo, Yuheng. "Impact on Biometric Identification Systems of COVID-19." Scientific Programming 2021 (December 2, 2021): 1–7. http://dx.doi.org/10.1155/2021/3225687.
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COVID-19 has had an inevitable impact on the daily life of people in 2020. Changes in behavior such as wearing masks have a considerable impact on biometric systems, especially face recognition systems. When people are aware of this impact, a comprehensive evaluation of this phenomenon is lacking. The purpose of this paper is to qualitatively evaluate the impact of COVID-19 on various biometric systems and to quantitatively evaluate face detection and recognition. The experimental results show that a real-world masked face dataset is essential to build an effective face recognition-based biometric system.
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KOPCZEWSKI, Marian, and Tomasz SMAL. "POSSIBILITIES FOR THE USE OF BIOMETRIC DATA IN SECURITY SYSTEMS." Journal of Science of the Gen. Tadeusz Kosciuszko Military Academy of Land Forces 186, no. 4 (October 2, 2017): 168–79. http://dx.doi.org/10.5604/01.3001.0010.7226.
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Possibilities for the use of biometric data are growing and hence their practical application is also increasing. Therefore, an important element to be considered in the design, construction and exploitation of systems using biometrics is the question of identifying a specific person and assigning him or her to the relevant data contained in the documents or databases. The ability and, in some cases, the need to use biometric data results from the growing use of information technology in everyday life and the ever increasing attempts to steal the identity of those using these technologies. Modern IT systems often have a high level of security in terms of protection and access to data, and in particular the management of security systems. The article presents an outline of the theory related to the possibility of using and applying biometric data to provide security and have the ability to inspect officers of various departments. The subject of analysis also considered the possibility of using security measures in the form of biometric data identification for the purpose of securing the security services.
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Lozhnikov, Pavel, and Samal Zhumazhanova. "Model of the "biometry-code" converter based on artificial neural networks for analysis of facial thermograms." Digital Technology Security, no. 2 (June 25, 2021): 154–65. http://dx.doi.org/10.17212/2782-2230-2021-2-154-165.
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Existing asymmetric encryption algorithms involve the storage of a secret private key, authorized access to which, as a rule, is carried out upon presentation of a password. Passwords are vulnerable to social engineering and human factors. Combining biometric security techniques with cryptography is seen as a possible solution to this problem, but any biometric cryptosystem should be able to overcome the small differences that exist between two different implementations of the same biometric parameter. This is especially true for dynamic biometrics, when differences can be caused by a change in the psychophysiological state of the subject. The solution to the problems is the use of a system based on the "biometrics-code" converter, which is configured to issue a user key after presentation of his/her biometric image. In this case, the key is generated in advance in accordance with accepted standards without the use of biometric images. The work presents results on using thermal images of a user for reliable biometric authentication based on a neural network "biometrics-code" converter. Thermal images have recently been used as a new approach in biometric identification systems and are a special type of biometric images that allow us to solve the problem of both the authentication of the subject and the identification of his psychophysiological state. The advantages of thermal imaging are that this technology is now becoming available and mobile, allowing the user to be identified and authenticated in a non-contact and continuous manner. In this paper, an experiment was conducted to verify the images of thermograms of 84 subjects and the following indicators of erroneous decisions were obtained: EER = 0.85 % for users in the "normal"state.
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Medina Salgado, César. "Biometric identification systems. An organizational control tool." Gestión y Estrategia 30 (July 1, 2006): 35–46. http://dx.doi.org/10.24275/uam/azc/dcsh/gye/2006n30/medina.
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Alay, Nada, and Heyam H. Al-Baity. "Deep Learning Approach for Multimodal Biometric Recognition System Based on Fusion of Iris, Face, and Finger Vein Traits." Sensors 20, no. 19 (September 27, 2020): 5523. http://dx.doi.org/10.3390/s20195523.
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With the increasing demand for information security and security regulations all over the world, biometric recognition technology has been widely used in our everyday life. In this regard, multimodal biometrics technology has gained interest and became popular due to its ability to overcome a number of significant limitations of unimodal biometric systems. In this paper, a new multimodal biometric human identification system is proposed, which is based on a deep learning algorithm for recognizing humans using biometric modalities of iris, face, and finger vein. The structure of the system is based on convolutional neural networks (CNNs) which extract features and classify images by softmax classifier. To develop the system, three CNN models were combined; one for iris, one for face, and one for finger vein. In order to build the CNN model, the famous pertained model VGG-16 was used, the Adam optimization method was applied and categorical cross-entropy was used as a loss function. Some techniques to avoid overfitting were applied, such as image augmentation and dropout techniques. For fusing the CNN models, different fusion approaches were employed to explore the influence of fusion approaches on recognition performance, therefore, feature and score level fusion approaches were applied. The performance of the proposed system was empirically evaluated by conducting several experiments on the SDUMLA-HMT dataset, which is a multimodal biometrics dataset. The obtained results demonstrated that using three biometric traits in biometric identification systems obtained better results than using two or one biometric traits. The results also showed that our approach comfortably outperformed other state-of-the-art methods by achieving an accuracy of 99.39%, with a feature level fusion approach and an accuracy of 100% with different methods of score level fusion.
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Ivanovas, Edgaras. "BIOMETRIC FEATURES IN PERSON RECOGNITION SYSTEMS." Mokslas - Lietuvos ateitis 2, no. 1 (February 28, 2010): 23–26. http://dx.doi.org/10.3846/mla.2010.005.
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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.
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Petrosyan, G., L. Ter-Vardanyan, and A. Gaboutchian. "MODELLING OF BIOMETRIC IDENTIFICATION SYSTEM WITH GIVEN PARAMETERS USING COLORED PETRI NETS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W4 (May 10, 2017): 145–50. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w4-145-2017.
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Biometric identification systems use given parameters and function on the basis of Colored Petri Nets as a modelling language developed for systems in which communication, synchronization and distributed resources play an important role. Colored Petri Nets combine the strengths of Classical Petri Nets with the power of a high-level programming language. Coloured Petri Nets have both, formal intuitive and graphical presentations. Graphical CPN model consists of a set of interacting modules which include a network of places, transitions and arcs. Mathematical representation has a well-defined syntax and semantics, as well as defines system behavioural properties. One of the best known features used in biometric is the human finger print pattern. During the last decade other human features have become of interest, such as iris-based or face recognition. The objective of this paper is to introduce the fundamental concepts of Petri Nets in relation to tooth shape analysis. Biometric identification systems functioning has two phases: data enrollment phase and identification phase. During the data enrollment phase images of teeth are added to database. This record contains enrollment data as a noisy version of the biometrical data corresponding to the individual. During the identification phase an unknown individual is observed again and is compared to the enrollment data in the database and then system estimates the individual. The purpose of modeling biometric identification system by means of Petri Nets is to reveal the following aspects of the functioning model: the efficiency of the model, behavior of the model, mistakes and accidents in the model, feasibility of the model simplification or substitution of its separate components for more effective components without interfering system functioning. The results of biometric identification system modeling and evaluating are presented and discussed.
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TANNIAN, MARK F., CHRISTINA SCHWEIKERT, and YING LIU. "A Systems Security Analysis of Issuance and Verification of Birth Documents Enhanced with DNA Profiles." Journal of Interconnection Networks 17, no. 01 (March 2017): 1740003. http://dx.doi.org/10.1142/s0219265917400035.
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The use of biometrics to enhance identification has been explored and utilized to various extents. DNA is the most reliable and stable biometric that remains unchanged throughout an individual’s lifetime. Advancements in DNA analysis, in terms of reduced cost and faster processing times, make the use of DNA as a biometric more feasible over time. Since DNA data is of a sensitive nature, privacy and ethical concerns would have to be carefully considered before large-scale adoption for use in identity documents. Birth certificates are a fundamental document used by a person for identification. However, it does not contain any means of authentication beyond possession of the document. This paper examines the security measures that would be required if birth certificates were embedded with DNA profile information. The U.S. FBI CODIS approach is referred to, being an established standard for human DNA profiling and identification. Effects on the issuance and verification network for birth certificate documents are explored, in addition to the security threats.
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Shurugin, Sergei V., Arif U. Matveev, and Evgeny V. Gritskevich. "DEVELOPMENT AND ANALYSIS OF A CONCEPTUAL MODEL OF BIOMETRIC INFORMATION FROM THE POINT OF VIEW OF THE EXISTING LEGISLATIVE AND REGULATORY FRAMEWORKS." Interexpo GEO-Siberia 6 (May 21, 2021): 321–27. http://dx.doi.org/10.33764/2618-981x-2021-6-321-327.
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The proposed work is devoted to the classification of biometric systems for recognizing subjects, which play an important role in modern information security systems, since they are currently one of the main means of identification and authentication of an individual. The classification schemes presented in this paper allow us to apply a systematic approach to the development of new methods of biometrics.
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Abraham, Jobin Reji. "Identification of Children Using HOG." International Journal for Research in Applied Science and Engineering Technology 10, no. 11 (November 30, 2022): 2014–21. http://dx.doi.org/10.22214/ijraset.2022.47773.
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Abstract: Adults often utilize biometric recognition for a variety of tasks that require a personal identification evidence to be validated. Children's biometric identification, however, is still a challenge. In addition to helping find lost children and their families, developing border control systems to stop child trafficking, and assisting electronic recordkeeping systems, addressing this issue helps safeguard children against identity theft and identity fraud. Researchers are gathering biometric data from newborns' fingerprints, irises, and outer ears in order to start creating biometric recognition systems for kids. Children's ear mode was implemented using the hardware and software that were previously utilized for adults. Existing hardware was utilized in iris mode to find iris pictures. In order to capture children's fingerprints and transform the pictures into a backdrop format that complies with current international standards for issuing and comparing minutiae, new image processing gear and software have been created. Based on analyzing the effectiveness of usage and measuring the amount of performance, the benefits and drawbacks of utilizing each of these strategies throughout the first year of life were compared. Recommendations for the usage of each approach were given, despite the fact that they weren't always best practices.
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Hendrawan, Muhammad Afif, Pramana Yoga Saputra, and Cahya Rahmad. "Identification of optimum segment in single channel EEG biometric system." Indonesian Journal of Electrical Engineering and Computer Science 23, no. 3 (September 1, 2021): 1847. http://dx.doi.org/10.11591/ijeecs.v23.i3.pp1847-1854.
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Nowadays, biometric modalities have gained popularity in security systems. Nevertheless, the conventional commercial-grade biometric system addresses some issues. The biggest problem is that they can be imposed by artificial biometrics. The electroencephalogram (EEG) is a possible solution. It is nearly impossible to replicate because it is dependent on human mental activity. Several studies have already demonstrated a high level of accuracy. However, it requires a large number of sensors and time to collect the signal. This study proposed a biometric system using single-channel EEG recorded during resting eyes open (EO) conditions. A total of 45 EEG signals from 9 subjects were collected. The EEG signal was segmented into 5 second lengths. The alpha band was used in this study. Discrete wavelet transform (DWT) with Daubechies type 4 (db4) was employed to extract the alpha band. Power spectral density (PSD) was extracted from each segment as the main feature. Linear discriminant analysis (LDA) and support vector machine (SVM) were used to classify the EEG signal. The proposed method achieved 86% accuracy using LDA only from the third segment. Therefore, this study showed that it is possible to utilize single-channel EEG during a resting EO state in a biometric system.
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Yang, Xiaopeng, Hui Zhu, Songnian Zhang, Rongxing Lu, and Xuesong Gao. "An Efficient and Privacy-Preserving Biometric Identification Scheme Based on the FITing-Tree." Security and Communication Networks 2021 (October 25, 2021): 1–15. http://dx.doi.org/10.1155/2021/2313389.
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Biometric identification services have been applied to almost all aspects of life. However, how to securely and efficiently identify an individual in a huge biometric dataset is still very challenging. For one thing, biometric data is very sensitive and should be kept secure during the process of biometric identification. On the other hand, searching a biometric template in a large dataset can be very time-consuming, especially when some privacy-preserving measures are adopted. To address this problem, we propose an efficient and privacy-preserving biometric identification scheme based on the FITing-tree, iDistance, and a symmetric homomorphic encryption (SHE) scheme with two cloud servers. With our proposed scheme, the privacy of the user’s identification request and service provider’s dataset is guaranteed, while the computational costs of the cloud servers in searching the biometric dataset can be kept at an acceptable level. Detailed security analysis shows that the privacy of both the biometric dataset and biometric identification request is well protected during the identification service. In addition, we implement our proposed scheme and compare it to a previously reported M-Tree based privacy-preserving identification scheme in terms of computational and communication costs. Experimental results demonstrate that our proposed scheme is indeed efficient in terms of computational and communication costs while identifying a biometric template in a large dataset.
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A, Saritha Haridas, and Kesavan Namboothiri T. "Ear Biometrics and Face Mask Detection Using Haar Features." International Journal of Engineering Research in Electronics and Communication Engineering 9, no. 7 (July 18, 2022): 5–10. http://dx.doi.org/10.36647/ijerece/09.07.a002.
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The world depends on systems to provide secure environments and services to the people. Biometrics authentication (or realistic authentication) is employed in applied science as a style of identification and access control. Biometric System for authentic identification of a private. My motto is to make a biometric system using the ear as the main object. It also has no changes as expression change The human ear are neither affected by expressions like faces are nor do need closer touching like finger-prints do, which is more useful in the situation where the protection mechanism is needed as like in the pandemic Covid19 situation. Ear biometrics appears to be an accurate approach to an ever increasing demand for security in the common spaces. Then the robust feature extraction method is often accustomed determine personality of some individuals, as an example terrorist at the airport terminals. Ear as biometrics is often used in multimodal systems to improve the performance of some other known biometrics. In this paper, a novel algorithm was proposed to do face mask detection and ear recognition using deep convolutional neural network and provide a visualization of the learned network. Also a temperature sensor is included. Only after the checking of facemask the subject is allowed to ear biometrics for more security reason.