SOFT BIOMETRIC AUTHENTICATION

Authors

  • Melisa Azizovic University of Novi Pazar, Serbia
  • Emrus Azizovic University of Novi Pazar, Serbia

Keywords:

Biometrics, soft biometrics, authentication, social pattern, emotional pattern, behavioral pattern

Abstract

Soft biometric authentication is the process of identifying or authenticating users based on characteristics that are less reliable than traditional biometric characteristics such as fingerprints or faces. Soft biometric authentication is a technology that uses different types of features and characteristics of users to determine whether they are a real user. These characteristics are commonly referred to as "soft" biometrics, as they differ from "hard" biometrics, which refer to physical characteristics such as fingerprints or the pupil of the eye. Examples of soft biometrics include characteristics such as handwriting, typing speed, voice characteristics, gestures, and other non-invasive and easily measurable characteristics. Soft biometric authentication is used in situations where traditional biometric characteristics are not reliable enough, or when the user does not want to provide personal information that is necessary for authentication. Soft biometric authentication plays an increasingly important role in the modern world, especially in the field of information technology. As technologies evolve, so do the risks of identity theft and hacker attacks. Soft biometric authentication provides an additional layer of security, helping to verify the user's identity based on various behavioral characteristics, making unauthorized access to the system difficult. This technology is increasingly used in banking, e-commerce, social media, health care and other areas where reliable user authentication is required. Soft biometric authentication also enables a better user experience, providing easier and faster access to systems and applications without the need for predefined passwords or other security codes. In addition, soft biometric authentication has the potential to be used in combination with other technologies such as machine learning and artificial intelligence to create advanced authentication systems that can adapt their actions based on user preferences and behavior. Soft biometric authentication has several advantages over traditional authentication methods. For example, users do not need to carry additional devices such as cards or keys, and they also do not need to remember passwords. This technology can also be useful in preventing fraud or hacking, as user behavior and environmental characteristics are difficult to fake. However, soft biometric authentication also has certain disadvantages, such as lower reliability compared to traditional authentication methods, the possibility of errors due to the variability of user characteristics and the environment, as well as the possibility of misuse of data on user characteristics. In this paper, we focused on the analysis of soft biometric authentication. First, we defined the term biometrics in order to follow the further content of the paper. We presented categories and analyzed security and privacy in soft biometric authentication.

Author Biography

Melisa Azizovic, University of Novi Pazar, Serbia

Department of Computer Science

References

Ashbourn, J. (2000). Biometrics: Advanced Identity Verification: The Complete Guide, Springer-Verlag, London,

Bigun, J., Fierrez, J., & Ortega-Garcia, J. (2009)."Biometrics and Identity Management", Springer,

Islam, M. T., & Kabir, A. B. M. A. H. (2019). "Soft Biometric Traits in Multimodal Biometric Systems: A Survey", Journal of Information Processing Systems, vol. 15, no. 2, pp. 327-356,

Iyengar, S. S., & Singh, S. K. (2018). "Behavioral Biometrics: A Comprehensive Survey", ACM Computing Surveys, vol. 51, no. 2, pp. 1-36,

Li, B., Xiong, X., & Noman, A. N. M. (2018). "Soft Biometrics: A New Approach to Enhance User Authentication", Future Internet, vol. 10, no. 1, pp. 1-16,

Patil, P. R., Karode, A. H., & Suralkar, D. S. R. (2017). Human skin detection using image fusion. International Journal of Electronics and Communication Engineering and Technology, 8(4), 13–21.

Rajasekar, V., Saračević, M., Hassaballah, M., Karabasevic, D., Stanujkic, D., Zajmovic, M., Tariq, U., Jayapaul, P. (2002). Efficient Multimodal Biometric Recognition for Secure Authentication Based on Deep Learning Approach, International Journal on Artificial Intelligence Tools, World Scientific.

Rhien-Lien, H., Mohamed Abdel - Mottabel, & Jain, A. K.. (2002). “Face Detection in Color Images”, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 5, pp. 696.706, May

Schneider, J., Franke, K., & Nickolay, B. (2000). Konzeptstudie - Biometrische Authentifikation. Technical report, Fraunhofer IPK Berlin, (in German).

Sobabe, A.-A., Djara, T., & Vianou, A. (2019). A Framework for Combination of Sequential Architecture and Soft Biometrics in Multibiometric Scores Fusion [Conference paper] 3rd International Conference on Bio-engineering for Smart Technologies, Paris, France. https://ieeexplore.ieee.org/abstract/document/8734247 .

Yan, J., Ross, A., & Noman, A. N. M. (2012). "Soft Biometrics for Personal Recognition Systems: A Survey", IEEE Transactions on Systems, Man, and Cybernetics, Part C ,vol. 42, no. 6, pp. 1241-1251

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Published

2023-06-01

How to Cite

Azizovic, M., & Azizovic, E. (2023). SOFT BIOMETRIC AUTHENTICATION. KNOWLEDGE - International Journal , 58(3), 481–487. Retrieved from http://ikm.mk/ojs/index.php/kij/article/view/6134