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Smartphone Security Using Swipe Behavior-based Authentication

Adnan Bin Amanat Ali1, Vasaki Ponnusamy1, Anbuselvan Sangodiah1, Roobaea Alroobaea2, N. Z. Jhanjhi3,*, Uttam Ghosh4, Mehedi Masud2

1 Department of Computer and Communication Technology, Universiti Tunku Abdul Rahman, Kampar, 31900, Malaysia
2 Department of Computer Science, College of Computers and Information Technology, Taif University, Taif, 21944, Saudi Arabia
3 School of Computer Science and Engineering (SCE), Taylor’s University, Subang Jaya, 47500, Malaysia
4 Vanderbilt University, Nashville, TN, 37240-0002, USA

* Corresponding Author: N. Z. Jhanjhi. Email:

Intelligent Automation & Soft Computing 2021, 29(2), 571-585.


Most smartphone users prefer easy and convenient authentication without remembering complicated passwords or drawing intricate patterns. Preferably, after one-time authentication, there is no verification of the user’s authenticity. Therefore, security and privacy against unauthorized users is a crucial research area. Behavioral authentication is an emerging security technique that is gaining attention for its uniqueness and transparency. In this paper, a behavior-based authentication system is built using swipe movements to continuously authenticate the user after one-time traditional authentication. The key feature is the selection of an optimal feature set for the swipe movement. Five machine learning classifiers are used, of which random forest is selected based on the best values of accuracy and F-measure. A real-time system is developed by shifting all of the computational power to a cloud server to overcome the smartphone’s computational limitations. The system is tested on three smartphones, and it is found that a minimum of seven swipes is sufficient to check user authenticity. In our experiments, the proposed feature set performs better than a state-of-the-art feature set.


Cite This Article

A. Bin Amanat Ali, V. Ponnusamy, A. Sangodiah, R. Alroobaea, N. Z. Jhanjhi et al., "Smartphone security using swipe behavior-based authentication," Intelligent Automation & Soft Computing, vol. 29, no.2, pp. 571–585, 2021.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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