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Jayabalan, M (2022) Application of Machine Learning to User Behavior-Based Authentication in Smartphone and Web. In: Applications of Machine Learning and Deep Learning for Privacy and Cybersecurity. IGI Global, pp. 73-94.
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Behavior Profiling V5.3.pdf - Published Version Download (529kB) | Preview |
Abstract
Authentication is the preliminary security mechanism employed in the information system to identify the legitimacy of the user. With technological advancements, hackers with sophisticated techniques easily crack single-factor authentication (username and password). Therefore, organizations started to deploy multi-factor authentication (MFA) to increase the complexity of the access to the system. Despite the MFA increasing the security of the digital service, the usable security should be given equal importance. The user behavior-based authentication provides a means to analyze the user interaction with the system in a non-intrusive way to identify the user legitimacy. This chapter presents a review of user behavior-based authentication in smartphones and websites. Moreover, the review highlights some of the common features, techniques, and evaluation criteria usually considered in the development of user behavior profiling.
| Item Type: | Book Section |
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| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Computer Science & Mathematics |
| Publisher: | IGI Global |
| SWORD Depositor: | A Symplectic |
| Date Deposited: | 22 Sep 2022 09:33 |
| Last Modified: | 22 Sep 2022 09:33 |
| DOI or ID number: | 10.4018/978-1-7998-9430-8.ch004 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/17655 |
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