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PaSOFuAC: Particle Swarm Optimization Based Fuzzy Associative Classifier for Detecting Phishing Websites

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Abstract

The increased availability of wireless handheld devices and smartphones has accelerated the use of Internet for various applications. However, this proliferated usage of Internet with its vulnerabilities causes people with deceptive intentions to gain financial advantages. Phishing is one such attack carried out by the forged websites to acquire the personal credentials of the online users. The state-of-the-art methods to mitigate the phishing attacks include black list, white list, and heuristic techniques. The heuristic techniques outperform the other techniques in detection accuracy for unknown attacks. Associative Classification (AC) is an emerging heuristic technique that uses Association Rule Mining for classification. The existing AC techniques require two threshold values, viz., minimum support and minimum confidence to generate the rules. Besides, the quantitative attributes are discretized into pre-specified intervals leading to a sharp boundary problem. Therefore, to address these issues, in this paper, a novel Particle Swarm Optimization based Fuzzy Associative Classifier (PaSOFuAC) is proposed for detecting the phishing websites. PaSOFuAC improves the detection accuracy by determining the best rule which has high Rule Gain Ratio to predict the class attribute and exploiting the fuzzy logic to overcome the sharp boundary problem. The proposed approach was tested with the traditional classifiers and other AC approaches with respect to various performance measures. The experimental results reveal that PaSOFuAC outperforms the other existing techniques for detecting the phishing websites.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology, Tiruchirappalli, India

    S. Priya, S. Selvakumar & R. Leela velusamy

  2. Indian Institute of Information Technology, Una (HP), Una, India

    S. Selvakumar

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  1. S. Priya
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Priya, S., Selvakumar, S. & velusamy, R.L. PaSOFuAC: Particle Swarm Optimization Based Fuzzy Associative Classifier for Detecting Phishing Websites. Wireless Pers Commun 125, 755–784 (2022). https://doi.org/10.1007/s11277-022-09576-3

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