Noor Syahirah, Nordin and Mohd Arfian, Ismail and Tole, Sutikno and Shahreen, Kasim and Rohayanti, Hassan and Zalmiyah, Zakaria and Mohd Saberi, Mohamad (2021) A comparative analysis of metaheuristic algorithms in fuzzy modelling for phishing attack detection. Indonesian Journal of Electrical Engineering and Computer Science, 23 (2). pp. 1146-1158. ISSN 2502-4752. (Published)
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Abstract
Phishing attack is a well-known cyber security attack that happens to many people around the world. The increasing and never-ending case of phishing attack has led to more automated approaches in detecting phishing attack. One of the methods is applying fuzzy system. Fuzzy system is a rule-based system that utilize fuzzy sets and fuzzy logic concept to solve problems. However, it is hard to achieve optimal solution when applied to complex problem where the process of identify the fuzzy parameter becomes more complicated. To cater this issue, an optimization method is needed to identify the parameter of fuzzy automatically. The optimization method derives from the metaheuristic algorithm. Therefore, the aim of this study is to make a comparative analysis between the metaheuristic algorithms in fuzzy modelling. The study was conducted to analyse which algorithm performed better when applied in two datasets: website phishing dataset (WPD) and phishing websites dataset (PWD). Then the results were obtained to show the performance of every metaheuristic algorithm in terms of convergence speed, and four metrics including accuracy, recall, precision, and f-measure.
| Item Type: | Article |
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| Uncontrolled Keywords: | Cyber security; fuzzy logic; Metaheuristic algorithm; Phishing attack detection; Phishing websites dataset; Website phishing dataset |
| Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Faculty/Division: | Faculty of Computing |
| Depositing User: | Miss. Ratna Wilis Haryati Mustapa |
| Date Deposited: | 23 Aug 2021 09:15 |
| Last Modified: | 23 Aug 2021 09:15 |
| URI: | http://umpir.ump.edu.my/id/eprint/31865 |
| Download Statistic: | View Download Statistics |
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