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Human Behavioral Identifiers
Published in S. Poonkuntran, Rajesh Kumar Dhanraj, Balamurugan Balusamy, Object Detection with Deep Learning Models, 2023
T. Suba Nachiar, T. Shanmuga Priya, P.R. Hemalatha, J.V. Anchitaalagammai
The usage of static biometrics or identifiers has increased over the years. Companies and organizations using this have raised serious concerns about the use of physical factors.Using only one physical biometric data point to authenticate a user at the time of login is fundamentally the same as adding a static second password, albeit one that can never be changed if compromised.Physical biometrics can be captured and are sold in many cases, utilized again or synthesized with fake IDs.This creates several issues, which have forced many large organizations like IBM to withdraw or scale back from facial recognition technologies.Physical biometrics are purely based on a static approach. The problem with static biometrics security based on several factors, like points captured in fixed images, is that even if the initial authentication is valid and done by the legitimate user, the integrity of the session gradually erodes over time. The only mode to restore it is to require additional authentication factors. But, continuing to ask users or clients for traditional attributes – passwords, facial recognition, fingerprints – is troublesome and causes significant resistance, leading to poor client experience.
A Survey of Artificial Intelligence Techniques Used in Biometric Systems
Published in Chiranji Lal Chowdhary, Intelligent Systems, 2019
C. N. Patill, E. Naresh, B. P. Vijay Kumar, Prashanth Kambli
Biometric-system identification and recognition method is based on the characteristics and unique identity of every individual. The characteristics and unique identity of every individual is based on physical and behavioral traits. In the biometric system there are some key advantages, like they are nontransferable, nonrepudiation, nonassumable, and gives more protection against the fraud identification and recognition. These technologies are successfully implemented in various real-time applications, such as the banking sector, financial institutions, government offices, and educational institutes, company identity management, and other identification and recognition purposes. There are some most commonly used biometric systems for the identification and recognition method, including facial recognition, palm vein recognition, iris recognition, fingerprint recognition, and voice recognition.
Acquisition and Computation for Data in Biometric System
Published in Karm Veer Arya, Robin Singh Bhadoria, The Biometric Computing, 2019
Biometrics refers to a method for measurement of human characteristics. Biometrics is basically used for authentication and identification of a human being. Multiple applications of biometrics also include identification of a person in groups that are under surveillance. Different traits used for authentication and identification are human physical appearance, habits and behavioral aspects. For a specific application, selection of the particular trait or multiple traits depends upon the accuracy desired and time constraint. For any application, a single biometric does not meet the requirement. Physiological biometrics is used in recognition system in which biometric data such as signature, face, speech, fingerprint, iris, retina, gait, hand and ear geometry, etc. are acquired from person and compared from the stored biometric data. There are many application of biometrics such as security purpose, identification of individual, crime prevention and airport security, in defense, smart cards, law enforcement and surveillance. Depending on the applications, it basically operates in two ways: verification and identification.
Deep learning framework for biometric authentication using retinal images
Published in Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2023
Jarina B. Mazumdar, S. R. Nirmala
Biometric authentication is extensively used in banking, forensics and several security applications such as access control, identification and surveillance. The retinal images are the most reliable biometric traits and are unique for each individual even for identical twins (Tower 1955). The blood vessel patterns of retina remain stable with time and no clinical expert can change this structure. Retina is situated at rear end of the eye, so it is very difficult to forge (Jain et al. 2004). Hence, the authentication system based on retinal images is reliable and accurate for person identification. Even though the retina possesses such enticing features in comparison to other biometric traits, it is rarely used. Because the image acquisition procedure is considered invasive and needs a comparatively high degree of user cooperation (e.g. eye glasses need to be removed) (Ahmed et al. 2014). Many high-definition retinal scanners are designed to improve the quality of acquired images, and with a reduced amount of acquisition time. This leads to generation of huge amount of data every day. Thus, more efficient tool for data analysis is required to carry out the authentication task. The retinal images that have been acquired may also be adversely affected by geometric transforms like rotation, translation and also a minor scaling due to the movement of the eye or head placing in front the scanner. So, the person authentication based on retinal images must be invariant to such deformities.
Casualty Identification with Dental Radiographs and Photographs
Published in IETE Journal of Research, 2023
B. Vijayakumari, M. Vasanthal, S. Dhivya Dharshini
People travel widely these days and the chance for them, to meet an accident is also potentially high. Casualty is a person who got injured or killed during an accident. Biometric is a metric related to the physical or behavioural characteristics of a human being. A biometric system is used to identify and authenticate a person based on the information, which are unique biological traits. There are various physiological biometric measurements such a fingerprint, face, hand, Iris, and DNA matching and also behavioural biometric measurements such as signature dynamics, keystroke dynamics, voice recognition, etc. Physiological measurements offer more stability throughout the lifetime of the individual (i.e.) they are not subjected to any level of stress, contrary to the identification of behavioural measurement. After an accident, the chance for damage to the physiological biometric measurement of the casualty, such as their fingerprint, face, and the iris, is high. So, the Dental Biometric has been chosen here for casualty identification. In Dental Biometric, the information from the dental structure of an individual is used to identify the casualty. It is now a revolutionized field in forensics that continues to aid in the identification of unknown human remains, which earned great fame.
Biometrics-Based Mobile User Authentication for the Elderly: Accessibility, Performance, and Method Design
Published in International Journal of Human–Computer Interaction, 2022
Kanlun Wang, Lina Zhou, Dongsong Zhang
Physiological-based biometrics tend to be secure and difficult to be stolen and forged but raise privacy concerns. Particularly, fingerprint recognition (e.g., Blanco-Gonzalo et al., 2015; Iqbal et al., 2020; Zheng et al., 2020) and face recognition (e.g., Corsetti et al., 2019; Shien & Singh, 2017; Wu & Wang, 2019) are the most prevalent physiological-based biometrics in use and have proven to be the most easy-to-use methods. Both are free of hearing and cognition requirements. Although fingerprint-based MUA also supports the elderly with vision impairments, it faces usability [e.g., those elderly users who have dry skin and skin tears (White-Chu & Reddy, 2011)] and security challenges [i.e., bypassed by using fingerprint residue or a gummy fingerprint (Matsumoto et al., 2002)]. Face recognition-based MUA also has its own vulnerabilities, such as presentation attacks [e.g., photo, video, and 3D mask attacks (Mohammadi et al., 2018)] and sensitivity to the background lighting (Wang et al., 2018). Additionally, the facial expressions of the elderly are limited (Corsetti et al., 2019).