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Journal articles on the topic 'Behavioural biometric'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Yaacob, Mohd Noorulfakhri, Syed Zulkarnain Syed Idrus, Wan Azani Wan Mustafa, Mohd Aminudin Jamlos, and Mohd Helmy Abd Wahab. "Identification of the Exclusivity of Individual’s Typing Style Using Soft Biometric Elements." Annals of Emerging Technologies in Computing 5, no. 5 (2021): 10–26. http://dx.doi.org/10.33166/aetic.2021.05.002.

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Biometric is used as a main security fence in a computer system. The unique characteristics of a person can be distinguished from each other. Human’s biometrics can be categorized into three types: morphological, biological and behavioural. Morphological biometrics uses physical features for recognition. Biological biometrics used to identify user based on biological features. Behavioural biometrics such as gender, culture, height and weight can be used as an additional security measure within a system. These biometric behavioural features are also known as soft biometric. This study uses soft

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Miss., Kamble Sunayana Nivrutti, Gund. V. D. Prof., and Kazi K. S. Prof. "Multimodal Biometrics Authentication System using Fusion of Fingerprint and Iris." International Journal of Trend in Scientific Research and Development 2, no. 6 (2018): 1282–86. https://doi.org/10.31142/ijtsrd18861.

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In the present era of information technology, there is a need to implement authentication and authorization techniques for security of resources. There are number of ways to prove authentication and authorization. But the biometric authentication beat all other techniques. Biometric techniques prove the authenticity or authorization of a human being based on his her physiological or behavioural traits. It also protects resources access from unauthorized users. We will develop a multimodal biometric identification system that represents a valid alternative to conventional approaches. In biometr

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S V, Kaaviya Sri. "Behavioural Biometric Security." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 02 (2025): 1–9. https://doi.org/10.55041/ijsrem41894.

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As e-Commerce continues and banking grows, shifting our shopping preference and money transferring from the physical to online marketplace, we leave behind digital traces of our personally identifiable details. For ex- ample, the merchant keeps record of your name and ad- dress; the payment processor stores your transaction details including account or card information, and every website you visit stores other information such as your device address and type. Cyber criminals keep robbing and use part of this information in fraud cases of identity, with tragic effects on the accountholders; but

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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 (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 propos

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Chahreddine, Medjahed, Rahmoun Abdellatif, Charrier Christophe, and Mezzoudj Freha. "A deep learning-based multimodal biometric system using score fusion." International Journal of Artificial Intelligence (IJ-AI) 11, no. 1 (2022): 65–80. https://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 propos

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Shinde, Krishna, and Sumegh Tharewal. "Development of Face and Signature Fusion Technology for Biometrics Authentication." International Journal of Emerging Research in Management and Technology 6, no. 9 (2018): 61. http://dx.doi.org/10.23956/ijermt.v6i9.86.

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The Biometrics system is getting popularity since last decade As per Information Technology industry demand. This techn-ology are satisfy authentication and authorization process needs. But the unimodal biometric system have own limitations. the limitation of unimodal, we can choosing the approach of multimodal biometric system. In this research paper choose the physiological model for face recognition and behavioural model for signature recognition. The recognition of face and signature used match score level fusion. In this fusion technology for secured authentication of person

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Ayanaba, Rasheed Abubakar. "Image-assisted Biometric Identification." Advances in Multidisciplinary and scientific Research Journal Publication 1, no. 1 (2022): 131–38. http://dx.doi.org/10.22624/aims/crp-bk3-p22.

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Biometrics is a rapidly developing technology that has seen widespread use in forensics applications such as criminal identification, secure access, and prison security. A biometric system is a pattern recognition system that recognizes a person by determining the authenticity of a physiological and/or behavioural feature that that person possesses. One of the most widely accepted biometrics utilized by humans in their visual interactions is image- assisted based (facial) biometric. Image-assisted biometric identification is the use of face recognition technology in capturing image of a unique

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Rasiah, Devinaga, and Yuen Yee Yen. "User acceptance of ATM biometric authentication." Global Journal of Computer Sciences: Theory and Research 10, no. 1 (2020): 11–17. http://dx.doi.org/10.18844/gjcs.v10i1.4748.

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Malaysia is amongst one of the first countries in the world to use biometrics as a standard in its identification cards and automatic teller machines (ATMs). Currently, there is a lack of studies in Malaysia and around the world that studied the user acceptance of ATM biometric authentication technology. All previous studies tended to overlook the user acceptance of ATM biometrics authentication which is an increasingly important mechanism to verify user identity in banking industry. Therefore, this study is carried out to examine the key factors of user acceptance of ATM biometric authenticat

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Oyekunle, Seun Michael, Anuoluwapo Deborah Popoola, Faith Hauwa Oluwapamilerin Kolo, Akinde Michael Ogunmolu, and Temilade Oluwatoyin Adesokan-Imran. "Intelligent Fraud Prevention Information Banking: A Data Governance- Centric Approach Using Behavioural Biometrics." Asian Journal of Research in Computer Science 18, no. 5 (2025): 525–43. https://doi.org/10.9734/ajrcos/2025/v18i5672.

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This study investigates the integration of behavioural biometrics and data governance in enhancing fraud prevention systems within the banking sector. Behavioural biometrics refers to the analysis of unique patterns in user interactions—such as typing rhythm, mouse movement, and touchscreen gestures—to authenticate identity continuously and unobtrusively. As financial fraud becomes more sophisticated, traditional rule-based systems are proving insufficient. This research addresses that gap by evaluating the performance and ethical deployment of intelligent fraud detection systems using real-wo

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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 (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

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Hina Ali and Saba Shaikh. "Comprehensive Review on Different Types of Biometrics and the Impact of Pandemic on Biometric Security." International Journal of Information Systems and Computer Technologies 3, no. 2 (2024): 70–79. http://dx.doi.org/10.58325/ijisct.003.02.0074.

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With the rapid rise of electronic crimes and their related difficulties, implementing a trustworthy user authentication system has become a critical responsibility for access control and data security. Because of this, the influence of biometrics in information security has become very popular. Everybody in this world has distinct physiological and behavioural features that set us apart from others. These unique features (or IDs) are used in biometrics to determine and authenticate people's identities. This research includes comparisons between two major categories of biometrics, namely physio

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Tamirah, Sharieff, Harmain Zoya, Smyrline R. Sarah, and Noorain Shafiya. "Redefining Security- Biometric Authentication System." Journal of Advances in Cryptography and Network Security 1, no. 1 (2025): 3–8. https://doi.org/10.5281/zenodo.14874057.

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<em>Biometric security has developed into a cutting- edge technology in security enhancement, particularly excelling in authentication and access control within the banking, healthcare, and government sectors. This innovative approach utilizes unique anatomical and behavioural characteristics, biometric imprints, facial analysis, iris patterns, and voice processing, rendering it more effective and practical than traditional password systems. The ongoing study focuses to assess the fundamental principles underlying security using biometric systems and examine their effectiveness in preventing u

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Adigun, Taiwo, Adedeji Adegbenle, Oludele Awodele, and Chibueze Ogbonna. "Optimizing Recurrent Neural Network with Bayesian Algorithm for Behavioural Authentication System." International Journal of Engineering and Computer Science 13, no. 09 (2024): 26373–90. http://dx.doi.org/10.18535/ijecs/v13i09.4886.

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Current studies on behavioural biometrics authentication have been focused on the use of deep learning and keystroke dynamics but the aspect of conscious optimization of the algorithm in order to obtain best outcome has not been considered. This study employed and incorporated Bayesian algorithm into Recurrent Neural Network to build a Keystroke Behavioural Biometric (KBB) authentication model used against social engineering attacks. The model begins with importing the keylogging dataset for data pre-processing, feature extraction, and RNN algorithm was used to build the KBB model. Hyperparame

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Rajasingh, J. Paul, and D. Sai Yaswanth. "Fingerprint Authentication." International Journal of Engineering and Advanced Technology 10, no. 5 (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 preve

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J, Paul Rajasingh, and Sai Yaswanth D. "Fingerprint Authentication." International Journal of Engineering and Advanced Technology (IJEAT) 10, no. 5 (2021): 87–89. https://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 preve

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K. Selsiya, Dr. D. Banumathy, Nijanthan, and Dr. G. Madasamyraja. "Person Authentication System Using Multimodal Biometrics." International Journal of Scientific Research in Science, Engineering and Technology 11, no. 3 (2024): 276–80. http://dx.doi.org/10.32628/ijsrset24113129.

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Biometrics is the automated process used to recognize human by measuring their behavioural and physiological characteristics. Biometrics are generally used either for verification The use of biometric for identification purposes requires that a particular biometric factor be unique for each individual that it can be calculated, and that it is invariant over time. Biometrics such as signatures, photographs, fingerprints, voiceprints and retinal blood vessel patterns all have noteworthy drawbacks. Although signatures and photographs are cheap and easy to obtain and store, they are impossible to

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Gore, Dayanand Bharat. "Comparative Study on Feature Extractions for Ear Recognition." International Journal of Applied Evolutionary Computation 10, no. 2 (2019): 8–18. http://dx.doi.org/10.4018/ijaec.2019040102.

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Biometrics includes the study of automatic methods for distinguishing human beings based on physical or behavioural traits. The problem of finding good biometric features and recognition methods has been researched extensively in recent years. This research considers the use of ears as a biometric for human recognition. In this article, basic feature extraction techniques are implemented such as Harris Feature, FAST Feature extraction and SURF Feature Extraction. All the images are taken from standard database and each image has different angles because of any criminal investigation, accident,

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Rahul, C. R., and A. Rengarajan. "Behavioural Biometrics as a User Authentication Mechanism in ISMS." International Journal of Innovative Research in Computer and Communication Engineering 12, no. 03 (2024): 1699–706. http://dx.doi.org/10.15680/ijircce.2024.1203054.

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Securing sensitive data and mitigating cyber threats necessitates robust user authentication mechanisms within Information Security Management Systems (ISMS). Conventional authentication approaches, such as passwords and static biometric identifiers, exhibit vulnerabilities, urging the adoption of more sophisticated solutions. Behavioral biometrics, which analyzes unique behavioral patterns like typing rhythm and mouse movements, offers a promising avenue for enhancing authentication security while optimizing user experience. This paper examines the integration of behavioral biometrics into IS

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Wong, Yee Leng, Mariyam Shamsuddin Siti, and Azman Hashim Nor. "Invariant behavioural based discriminationfor individual representation." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 1 (2021): 736–44. https://doi.org/10.11591/ijece.v11i1.pp736-744.

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Writer identification based on cursive words is one of the extensive behavioural biometric that has involved many researchers to work in. Recently, its main idea is in forensic investigation and biometric analysis as such the handwriting style can be used as individual behavioural adaptation for authenticating an author. In this study, a novel approach of presenting cursive features of authors is presented. The invariants-based discriminability of the features is proposed by discretizing the moment features of each writer using biometric invariant discretization cutting point (BIDCP). BIDCP is

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Manikis, Georgios C., Marios Spanakis, and Emmanouil G. Spanakis. "Personalized Mobile eHealth Services for Secure User Access Through a Multi Feature Biometric Framework." International Journal of Reliable and Quality E-Healthcare 8, no. 1 (2019): 40–51. http://dx.doi.org/10.4018/ijrqeh.2019010104.

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Humans have various features that differentiates one person from another which can be used to identify an individual for security purposes. These biometrics can authenticate or verify a person's identity and can be sorted in two classes, physiological and behavioural. In this article, the authors present their results of experimentation on publicly available facial images and the efficiency of a prototype version of SpeechXRays, a multi-modal biometric system that uses audio-visual characteristics for user authentication in eHealth platforms. Using the privacy and security mechanism provided,

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Leng, Wong Yee, Siti Mariyam Shamsuddin, and Nor Azman Hashim. "Invariant behavioural based discrimination for individual representation." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 1 (2021): 736. http://dx.doi.org/10.11591/ijece.v11i1.pp736-744.

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Writer identification based on cursive words is one of the extensive behavioural biometric that has involved many researchers to work in. Recently, its main idea is in forensic investigation and biometric analysis as such the handwriting style can be used as individual behavioural adaptation for authenticating an author. In this study, a novel approach of presenting cursive features of authors is presented. The invariants-based discriminability of the features is proposed by discretizing the moment features of each writer using biometric invariant discretization cutting point (BIDCP). BIDCP is

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Boyraz, Fatih Talha. "It is not just a click: protection of in-game behaviour data as biometric data under the GDPR." Interactive Entertainment Law Review 7, no. 1 (2024): 12–24. http://dx.doi.org/10.4337/ielr.2024.01.02.

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This article investigates the potential classification of players’ in-game behaviour data from basic computer peripherals, like keyboards and mouses (behavioural telemetry), as biometric data under the General Data Protection Regulation (GDPR). Modern technologies allow these types of data to reveal a wealth of personal information, including age, gender, emotional states, collaboration abilities, problem-solving skills, economic status, consumption habits, and character traits. The analysis is structured into three sections: understanding the nature of in-game behaviour data, assessing its al

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Jain, Anil K., and Arun Ross. "Bridging the gap: from biometrics to forensics." Philosophical Transactions of the Royal Society B: Biological Sciences 370, no. 1674 (2015): 20140254. http://dx.doi.org/10.1098/rstb.2014.0254.

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Biometric recognition, or simply biometrics, refers to automated recognition of individuals based on their behavioural and biological characteristics. The success of fingerprints in forensic science and law enforcement applications, coupled with growing concerns related to border control, financial fraud and cyber security, has generated a huge interest in using fingerprints, as well as other biological traits, for automated person recognition. It is, therefore, not surprising to see biometrics permeating various segments of our society. Applications include smartphone security, mobile payment

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Jassim, Marwa Fadhel, Wafaa mohammed Saeed Hamzah, and Abeer Fadhil Shimal. "Biometric iris templates security based on secret image sharing and chaotic maps." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 1 (2022): 339. http://dx.doi.org/10.11591/ijece.v12i1.pp339-348.

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Biometric technique includes of uniquely identifying person based on their physical or behavioural characteristics. It is mainly used for authentication. Storing the template in the database is not a safe approach, because it can be stolen or be tampered with. Due to its importance the template needs to be protected. To treat this safety issue, the suggested system employed a method for securely storing the iris template in the database which is a merging approach for secret image sharing and hiding to enhance security and protect the privacy by decomposing the template into two independent ho

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Marwa, Fadhel Jassim, mohammed Saeed Hamzah Wafaa, and Fadhil Shimal Abeer. "Biometric iris templates security based on secret image sharingand chaotic maps." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 1 (2022): 339–48. https://doi.org/10.11591/ijece.v12i1.pp339-348.

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Biometric technique includes of uniquely identifying person based on their physical or behavioural characteristics. It is mainly used for authentication. Storing the template in the database is not a safe approach, because it can be stolen or be tampered with. Due to its importance the template needs to be protected. To treat this safety issue, the suggested system employed a method for securely storing the iris template in the database which is a merging approach for secret image sharing and hiding to enhance security and protect the privacy by decomposing the template into two independent ho

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D’Amelio, Alessandro, Sabrina Patania, Sathya Bursic, Vittorio Cuculo, and Giuseppe Boccignone. "Using Gaze for Behavioural Biometrics." Sensors 23, no. 3 (2023): 1262. http://dx.doi.org/10.3390/s23031262.

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A principled approach to the analysis of eye movements for behavioural biometrics is laid down. The approach grounds in foraging theory, which provides a sound basis to capture the uniqueness of individual eye movement behaviour. We propose a composite Ornstein-Uhlenbeck process for quantifying the exploration/exploitation signature characterising the foraging eye behaviour. The relevant parameters of the composite model, inferred from eye-tracking data via Bayesian analysis, are shown to yield a suitable feature set for biometric identification; the latter is eventually accomplished via a cla

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Ejaz, Umair, Pratik Bhikhubhai Panchal, S. A. Mohaiminul Islam, and Aidar Imashev. "Behaviour Biometrics Using AI for Continuous Authentication Systems." Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023 8, no. 02 (2025): 53–64. https://doi.org/10.60087/jaigs.v8i02.386.

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Behaviour-based continuous authentication systems like those that utilise an individual user's typing rhythm and device usage behaviour patterns have much potential over password-based schemes since they do not require an individual user to memorise passwords. Irrespective of the progress in biometric technologies, many systems are still susceptible to more complex attacks, and the decision between security and usability has been a perennial struggle for researchers and practitioners. This paper offers a powerful continuous authentication system based on AI and behavioural biometrics, enhancin

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Hatture, Sanjeeva Kumar M., and Shweta Policepatil. "Masquerade Attack Analysis for Secured Face Biometric System." International Journal of Recent Technology and Engineering (IJRTE) 10, no. 2 (2021): 225–32. http://dx.doi.org/10.35940/ijrte.b6309.0710221.

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Biometrics systems are mostly used to establish an automated way for validating or recognising a living or nonliving person's identity based on physiological and behavioural features. Now a day’s biometric system has become trend in personal identification for security purpose in various fields like online banking, e-payment, organizations, institutions and so on. Face biometric is the second largest biometric trait used for unique identification while fingerprint is being the first. But face recognition systems are susceptible to spoof attacks made by nonreal faces mainly known as masquerade

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Shweta, Policepatil, and Kumar M. Hatture Sanjeeva. "Masquerade Attack Analysis for Secured Face Biometric System." International Journal of Recent Technology and Engineering (IJRTE) 10, no. 2 (2021): 225–32. https://doi.org/10.35940/ijrte.B6309.0710221.

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Biometrics systems are mostly used to establish an automated way for validating or recognising a living or nonliving person's identity based on physiological and behavioural features. Now a day’s biometric system has become trend in personal identification for security purpose in various fields like online banking, e-payment, organizations, institutions and so on. Face biometric is the second largest biometric trait used for unique identification while fingerprint is being the first. But face recognition systems are susceptible to spoof attacks made by nonreal faces mainly known as m

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Haitham, Salman Chyad, and Ali Mustafa Raniah. "Subject Review: Palm Print Biometric Authentication System for Security Applications." International Journal of Computer Science and Mobile Applications 10, no. 7 (2022): 8–15. https://doi.org/10.5281/zenodo.6874686.

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Biometric authentication offers an authoritative and accurate approach in access control to identifying or verifying the identity of the individual using the system, through their behavioural and physical traits such as palm print, face, finger print, voice, iris etc. The field of Security, Forensics, and Banking pays great attention to biometrics. Individual traits cannot be forget or missing as compared passwords to and keys. They are also being much complicated to copy. For this reason biometric security systems are considered to be safer and very secure than conventional security systems.

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Dipti Yadav. "Improving Recognition Accuracy in Multimodal Biometric Systems: A Study on Facial Traits and Fusion Strategies." Journal of Information Systems Engineering and Management 10, no. 12s (2025): 166–78. https://doi.org/10.52783/jisem.v10i12s.1771.

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Multimodal biometric systems are gaining prominence for their ability to enhance recognition accuracy and system security by integrating multiple biometric modalities. This study focuses on improving recognition accuracy through the effective utilization of facial traits and fusion strategies in multimodal systems. Facial traits, including features such as eyes, nose, lips, and chin, offer unique identification markers, but their performance can be hindered by factors like aging, lighting conditions, and variations in pose. To address these challenges, the integration of facial traits with oth

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Özbek, Mehmet Erdal. "A flexible approach for biometric menagerie on user classification of keystroke data." Journal of Electrical Engineering 74, no. 1 (2023): 23–31. http://dx.doi.org/10.2478/jee-2023-0003.

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Abstract Biometric systems aim to provide reliable authentication and verification of users. The behaviour of the users may alter the authentication performance when accessing these systems. Therefore, clustering users based on their actions is crucial. A biometric menagerie defines and labels user groups statistically according to their variability. However, determining groups is a fuzzy process and it may lead to inconsistencies. In this work, a novel and flexible approach is introduced based on the classification performance of the users data collected in a database without imposing any oth

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Nishiuchi, Nobuyuki, Shungo Komatsu, and Kimihiro Yamanaka. "Biometric verification using the motion of fingers: a combination of physical and behavioural biometrics." International Journal of Biometrics 2, no. 3 (2010): 222. http://dx.doi.org/10.1504/ijbm.2010.033387.

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Mattoo, Iqra, and Parul Agarwal. "Iris Biometric Modality: A Review." Oriental journal of computer science and technology 10, no. 2 (2017): 502–6. http://dx.doi.org/10.13005/ojcst/10.02.35.

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Biometric Recognition is the most suitable and informed identification method which is used in different fields due to its uniqueness of the countless behavioural and physiological traits like hand geometry, finger prints, iris recognition, face recognition, handwriting, voice recognition, etc. Iris recognition system is widely being used as it has inherently distinctive patterns that provide a robust method for the identification purpose. Different nations have already started to use biometric recognition system for the identification purposes including patient identification, border security

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Mawlood, Zhyar Q., and Azhin T. Sabir. "Human gait-based gender classification using neutral and non-neutral gait sequences." Innovaciencia Facultad de Ciencias Exactas Físicas y Naturales 7, no. 1 (2019): 1–13. http://dx.doi.org/10.15649/2346075x.689.

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A biometric system offers automatic identification of an individual basedon characteristic possessed by the individual. Biometric identification systems are often categorized as physiological or behavioural characteristics.Gait as one of the behavioural biometric recognition aims to recognizean individual by the way he/she walk. In this paper we propose genderclassification based on human gait features using wavelet transform andinvestigates the problem of non-neutral gait sequences; Coat Wearing andcarrying bag condition as addition to the neutral gait sequences. We shallinvestigate a new set

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Ercin, Berk, and Abdulkadir Karacı. "Real-Time Identification from Gait Features Using Cascade Voting Method." Applied Computer Systems 26, no. 2 (2021): 164–72. http://dx.doi.org/10.2478/acss-2021-0020.

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Abstract There are several biometric methods for identification. These are generally classified under two main groups as physiological and behavioural biometric methods. Recently, methods using behavioural biometric features have gained popularity. Identification made using gait pattern is also one of these methods. The present study proposes a machine learning based system performing identification in real time via gait features using a Kinect device. The data set is composed of 23 individuals’ skeleton model data obtained by the authors. From these data, 147 handcrafted features have been ex

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Kenward, R. E., and J. M. Tonkin. "Red and Grey squirrels: some behavioural and biometric differences." Journal of Zoology 209, no. 2 (1986): 279–81. http://dx.doi.org/10.1111/j.1469-7998.1986.tb03583.x.

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Bhardwaj, Ishan, Narendra D. Londhe, and Sunil K. Kopparapu. "A Novel Behavioural Biometric Technique for Robust User Authentication." IETE Technical Review 34, no. 5 (2016): 478–90. http://dx.doi.org/10.1080/02564602.2016.1203271.

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Демчишак, Р.Ю. "ПЕРСПЕКТИВИ БІОМЕТРИЧНОЇ ІДЕНТИФІКАЦІЇ У РАМКАХ КРИМІНАЛІСТИЧНОЇ РЕЄСТРАЦІЇ". Наукові записки Львівського університету бізнесу та права. Серія економічна. Серія юридична, № 29 (30 червня 2021): 148–54. https://doi.org/10.5281/zenodo.5651700.

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The article explores the prospects of using different methods of biometric identification during forensic registration. The author established that biometric data, together with the appropriate technical means by which identification is carried out, can become an integral part of the system of information and technical support of forensic registration. The author clarified the identification of biometric identification methods. Two groups of biometric identification methods are analyzed, namely: static and dynamic. Static methods of biometric identification include face recognition ("auto

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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 sy

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Thangamanimaran, Dhileepan, M. Sharat Chandar, and S. Chandia. "Optimization of biometric recognition using cuckoo search algorithm: a preliminary version for minutia based fingerprint identification." International Journal of Engineering & Technology 7, no. 1.1 (2017): 43. http://dx.doi.org/10.14419/ijet.v7i1.1.8920.

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Currently Behavioural Biometrics is the most widely used means of security. Though Behavioural Biometrics is highly reliable and secure, the data handling process is quite complex. This Problem can be solved by optimizing the process using cuckoo search algorithm.This Paper seeks to optimize the process of fingerprint matching by using an optimal algorithm. The Minutiae in the form of a matrix is extracted from a fingerprint. The Matrix is then split into smaller matrices with increasing dimension and then compared. The matrix with least dimension it is matched. If the Match is true then the v

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Meng, Weizhi, Duncan S. Wong, and Lam-For Kwok. "The effect of adaptive mechanism on behavioural biometric based mobile phone authentication." Information Management & Computer Security 22, no. 2 (2014): 155–66. http://dx.doi.org/10.1108/imcs-09-2013-0062.

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Purpose – This paper aims to design a compact scheme of behavioural biometric-based user authentication, develop an adaptive mechanism that selects an appropriate classifier in an adaptive way and conduct a study to explore the effect of this mechanism. Design/methodology/approach – As a study, the proposed adaptive mechanism was implemented using a cost-based metric, which enables mobile phones to adopt a less costly classifier in an adaptive way to build the user normal-behaviour model and detect behavioural anomalies. Findings – The user study with 50 participants indicates that our propose

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Wells, Alec, and Aminu Bello Usman. "Trust and Voice Biometrics Authentication for Internet of Things." International Journal of Information Security and Privacy 17, no. 1 (2023): 1–28. http://dx.doi.org/10.4018/ijisp.322102.

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In recent years, IoT adoption has been higher, and this causes lots of security concerns. One of the fundamental security concerns in IoT adoption is the question, “Are you who you say you are?” Thus, authentication forms the gateway for a secure communication system with IoT. So far, the human voice is one of the most natural, non-intrusive, and convenient behavioural biometric factors compared to other biometric authentication methods. Despite the non-intrusive characteristics of voice as a biometric authentication factor when accessing IoT technologies, there is a concern of a general socie

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Nagtode, Priti. "Research Paper on Transformative Innovations in Identity Verification and Recognition." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem35159.

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Integrating real-time human detection into identity authentication greatly improves both security and user experience. This strategy decreases fraud risk by analysing physiological and behavioural markers such as facial and eye movements. Its implementation in financial, healthcare, e-commerce, and law enforcement sectors promise to strengthen security measures. Although obstacles exist, the benefits of this human-centered approach are significant, paving the path for a safer digital future. Keywords: Identity verification, biometric authentication, digital security, real-time human detection,

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Nagtode, Priti. "Revolutionizing Identity Verification and Recognition." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem34580.

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The innovative integration of real-time human detection improves both security and user experience in identity authentication. This approach improves authentication processes by analysing physiological and behavioural indicators such as face movements and eye movements, hence reducing fraud risks. Its deployment across sectors promises to enhance security in finance, healthcare, e-commerce, and law enforcement. Despite the hurdles, the benefits of this human-centered approach are enormous, indicating a more secure digital future. Keywords— Identity verification, live human detection, digital s

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Adegbenle, Adedeji, Oludele Awodele, Chibueze Ogbonna, and Taiwo Adigun. "A Secured Keystroke-Based Model for Preventing Social Engineering Attacks using Recurrent Neural Network." International Journal of Computer Science and Mobile Computing 13, no. 10 (2024): 1–11. http://dx.doi.org/10.47760/ijcsmc.2024.v13i10.001.

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Among several authentication problems, preventing social engineering attacks using behavioural biometric approach has not received the required attention especially with focus on keystroke dynamics. This study aims to leverage the power of deep learning for more accurate and robust continuous authentication based on typing patterns. The proposed framework for this study utilized deep learning algorithm for behavioural biometrics authentication using Keystroke dynamics. The deep learning model was developed using Recurrent Neural Network (RNN) algorithm and was optimized was to obtain a better

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Olabode, Olatubosun, AdeniyiJide Kehinde, Akinyede Olufemi, Oluwadare A. Samuel, and Fasoranbaku A. Olusoga. "A SIGNATURE IDENTIFICATION SYSTEM WITH PRINCIPAL COMPONENT ANALYSIS AND STENTIFORD THINNING ALGORITHMS." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 14, no. 9 (2015): 6074–84. http://dx.doi.org/10.24297/ijct.v14i9.7079.

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Several biometric security systems have been implemented. Biometric is the use of a personâ€™s physiological or behavioural characteristics to identify the individual. An example of behavioural method of biometric is signature identification. Signature identification is the use of handwritten signature to identify a person. This paper attempt design and implement an algorithm for handwritten signature identification. The signature identification system consists of signature acquisition, preprocessing, features extraction and matching stages. Signature acquisition can be either online or offlin

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Pavan, Kumar K., E. S. N. Krishna Prasad P., V. Ramakrishna M., and D. C. N. Prasad B. "Feature Extraction using Sparse SVD for Biometric Fusion in Multimodal Authentication." International Journal of Network Security & Its Applications (IJNSA) 5, no. 4 (2013): 83–94. https://doi.org/10.5281/zenodo.4496103.

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Token based security (ID Cards) have been used to restrict access to the Secured systems. The purpose of Biometrics is to identify / verify the correctness of an individual by using certain physiological or behavioural traits associated with the person. Current biometric systems make use of face, fingerprints, iris, hand geometry, retina, signature, palm print, voiceprint and so on to establish a person’s identity. Biometrics is one of the primary key concepts of real application domains such as aadhar card, passport, pan card, etc. In this paper, we consider face and fingerprint pattern

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Tehseen, Mehraj, Aman Sheheryar Mir, Ahmed Lone Sajaad, and H. Mir A. "A critical insight into the identity authentication systems on smartphones." Indonesian Journal of Electrical Engineering and Computer Science 13, no. 3 (2019): 982–89. https://doi.org/10.11591/ijeecs.v13.i3.pp982-989.

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The advancement of computing power on mobile devices and their popularity among people in performing sensitive data exchange is uncovering an urgent need for a highly secure solution than the existing ones. The need for such a security solution persists that should be able to thwart not only the contemporary threats but also offer continued support without bowing down to progression in technology. Though some security solutions have been contemplated, a lack of standardised or absolute security solution which can provide a feasible and secure solution to mobile phones exists. In this paper, a

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Gursoy, Mehmet Ismail. "Biometric Authentication Based on EMG Hand Gestures Signals Using CNN." Elektronika ir Elektrotechnika 30, no. 2 (2024): 54–62. http://dx.doi.org/10.5755/j02.eie.33777.

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Biometric identification systems are increasingly important today compared to traditional recognition/classification systems. Electromyography (EMG) signals and person identification/classification systems are preferred for high-security systems as they include physiological and behavioural movements. This study investigates biometric EMG signals based on convolutional neural networks (CNNs) and personal identification/classification systems. Bioelectric signals were recorded at six different wrist movements from five volunteer participants with a four-channel EMG device. To determine the spec

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