By: KV Sai Mounish, Department of computer science and technology, Student of computer science and technology, Madanapalle Institute Of Technology and Science, 517325, Angallu, Andhra Pradesh.
ABSTRACT –
Biometric security since its introduction has been taken through different enhancements as a result of technology as well as growing need for secure means of user identification. The current paper aims at illustrating the evolution of biometric security beginning with the first fingerprint identifying devices followed by sophisticated behavioral biometrics. Originally triggered from the use of fingerprints and iris scans, biometric security is today limited to those biometrics which are dynamic and can take into consideration the surrounding context, like voice recognition process, analysis of the keystroke dynamics as well as gait analysis. Such evolution is observed in the development of new solutions and services where more reliable, convenient, and diverse security is required considering today’s increased threats. The concept of this article will be to discuss the scientific advances in the field of biometrics, the present uses, and the possible future developments of using biometrics for security, as well as the consequences found in the aspects of privacy, protection, and comfort.
KEYWORDS –
Biometric Security, User Identification, Fingerprint, Evolution, Recognition, Privacy, Reliable.
INTRODUCTION –
As the modern society shifts to the digital environment the security issues like breaking into someone’s account or identity theft become more and more acute; consequently, more demands were made to complex and secure means of authentication. Biometric security, in which an individual’s physiological and/or behavioral traits are used in the confirmation process, has undergone tremendous advancement in the past few years. Starting from the concept of fingerprint recognition, which marked the beginning of the so-called biometrics, this area has evolved and developed, and is currently based on various types of biometric modalities. This article provides a detailed description on the history of biometric security with an indication into the current security practices such as mechanical fingerprinting all the way to the modern security practices within behavioral biometrics[1]. Analyzing this progression will allow to answer the questions of how the development of technology comprised the possibilities of biometric system and how biometric system further improves the security and overcomes the issues of privacy and convenience.
From Fingerprint to Facial Recognition
This paper will reveal the historical journey of biometric security from being innovative to what it is today together with the various inventions that have come along the way. This section traces the historical development of biometric authentication methods, highlighting key milestones and shifts in technology: This section traces the historical development of biometric authentication methods, highlighting key milestones and shifts in technology:
Early Beginnings: Fingerprint Recognition: the concept of fingerprinting is almost as old as crime itself, the initial practice of fingerprinting began around the late nineteenth and the early twentieth century[2]. Sir Francis Galton’s findings on the individuality of fingerprints and the utilization of fingerprints in criminal recognition by Henry Faulds are the foundation of current biometrics. This biometric parameter gained popularity in police forces and then in civil uses paving way to the next innovations.
The evolution of Biometrics is explained in Figure 1.
Advancements in Physiological Biometrics
When the technology advanced, other physiological parameters also got incorporated into the biometric systems[3]. Biometrics known as iris scanning that was invented in the eighties by Dr, John Daugman, and facial recognition technologies became possible substitutes to fingerprinting. Such systems provided new techniques for identification and authentication involving various features including the irises of the eyes and facial features.
Digital and Automated systems in corporate America
Thus, biometric systems have been incorporated into digital and automated technologies since the 1990s and up to the beginning of the 2000s. The computerized fingerprint matching systems have been introduced and the automatic facial recognition technologies brought improvement in the different areas of usage, security and identification, banking, and border control among others.
Integration and Expansion
In the recent past, the biometric security has stepped up a notch through use of multiple modes of biometrics[4]. Fingerprint, facial, and iris recognition together with other solutions like voice recognition and behavioral composites have made new forms of tighter systems. It resolves the issues associated with particular modalities and improves security as a whole.
The Rise of Behavioral Biometrics
Behavioral biometrics is a step up from general biometric security as this relies principally on physiological parameters, obtained a single time in man’s life. This section explores the rise of behavioral biometrics, examining their current applications, advantages, challenges, and future prospects: The following section will unveil several Research Questions related to behavioral biometrics: This section focuses on the behavioral biometrics today, their uses, benefits, limitations, and possibilities for tomorrow[5].
Introduction to Behavioral Biometrics
Behavioral biometrics are behavioral patterns of a particular person and do not therefore refer to fingerprints, palm prints or anything of that nature. In contrast to the previously used systems that depend on such measurable parameters as fingerprints, facial recognition, or others, behavioral biometrics follow how one or another particular person communicates with certain devices and systems, which is in fact more liberal and has the context into account.
Contemporary Approaches Identified in the Literature of Behavioral Biometrics
Keystroke Dynamics: A typing biometrics that relies on typing speed, pressure and the rhythm in order to type the users to the next level. This method is rather effective for online types of the application and can produce a continuous free flow of authentications when the users are actively in touch with the digital environments.
Voice Recognition: Speech Dactyloscopy; An individual can easily be distinguished regarding the pitch of the voice, its tone quality, pitch and so on. It is applied in various spheres and life facets, for example, utilization of voice consciousness to virtual counselors and customers.
Gait Analysis: Gait recognition; that entails using the way that a person walks to identify them. Apart from the latter, gait analysis is less used but could be beneficial when it comes to security and health screening.
CONCLUSION –
The emergence of biometric security that started with merely the ability to read fingerprints to the present-day behavioral biometrics is a proof that this area is very vibrant. Thus, over the years, the techniques of biometric authentication have also evolved, which has brought the transition from the strictly physiological to the more dynamic and context-sensitive. The old types of biometric system such as fingerprint and iris recognition created a platform for the latest developments in the field of biometric system such as face recognition and other behavioral biometric system like voice, keyboard pressure, and walking style. Notably, behavioral biometric systems present a major innovation in terms of the overall continuum of resumeless, continuous and natural, and intelligent approaches to security. Besides, the above methods improve the precision of biometric systems and meet the increasing demand for invisible and integrated security solutions. Other shortcomings associated with WSNs include accuracy issue, privacy issue, and systems interface with the existing systems.
As for the future prospects, the expansion of application areas of AI, machine learning, and wearable devices will continue to advance the development of biometric systems. Further development of the field is the key to its growth, though the procedures should not be deprived of the principles of the protection of users’ privacy and ethical perspective at the same time. Biometrics’ future reveals that the coming years will become the time when they combine several methods, providing stronger and safer authentications for the world that is gradually shifting towards the digital environment. To summarize thus, the shift from ordinary biometrics to advanced biometrics clearly and distinctively indicates that the process of protecting personal and sensitive data is on the enhancement. Such understanding sheds light on the current developments in biometric security and the possible future progression of the subject for further awareness on the sustainable research and innovations in security domain.
REFERENCES –
- I. Stylios, S. Kokolakis, O. Thanou, and S. Chatzis, “Behavioral biometrics & continuous user authentication on mobile devices: A survey,” Inf. Fusion, vol. 66, pp. 76–99, Feb. 2021, doi: 10.1016/j.inffus.2020.08.021.
- M. Smith and S. Miller, “The Rise of Biometric Identification: Fingerprints and Applied Ethics,” in Biometric Identification, Law and Ethics, M. Smith and S. Miller, Eds., Cham: Springer International Publishing, 2021, pp. 1–19. doi: 10.1007/978-3-030-90256-8_1.
- S. Dargan and M. Kumar, “A comprehensive survey on the biometric recognition systems based on physiological and behavioral modalities,” Expert Syst. Appl., vol. 143, p. 113114, Apr. 2020, doi: 10.1016/j.eswa.2019.113114.
- S. Manikandan, M. Rahaman, and Y.-L. Song, “Active Authentication Protocol for IoV Environment with Distributed Servers,” Comput. Mater. Contin., vol. 73, no. 3, pp. 5789–5808, 2022, doi: 10.32604/cmc.2022.031490.
- L. Triyono, R. Gernowo, P. Prayitno, M. Rahaman, and T. R. Yudantoro, “Fake News Detection in Indonesian Popular News Portal Using Machine Learning For Visual Impairment,” JOIV Int. J. Inform. Vis., vol. 7, no. 3, pp. 726–732, Sep. 2023, doi: 10.30630/joiv.7.3.1243.
- Kaur, M., Singh, D., Kumar, V., Gupta, B. B., & Abd El-Latif, A. A. (2021). Secure and energy efficient-based E-health care framework for green internet of things. IEEE Transactions on Green Communications and Networking, 5(3), 1223-1231.
- Zamzami, I. F., Pathoee, K., Gupta, B. B., Mishra, A., Rawat, D., & Alhalabi, W. (2022). Machine learning algorithms for smart and intelligent healthcare system in Society 5.0. International Journal of Intelligent Systems, 37(12), 11742-11763.
Cite As
Mounish K.V.S. (2024) Evolution of Biometrics from Fingerprint to Behavior Biometrics, Insights2Techinfo, pp. 1