Fuzzy modelling using firefly algorithm for phishing detection
A fuzzy system is a rule-based system that uses human experts’ knowledge to make a particular decision, while fuzzy modeling refers to the identification process of the fuzzy parameters. To generate the fuzzy parameters automatically, an optimization method is needed. One of the suitable methods pro...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
ASTES Publishers
2019
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/29847/1/Fuzzy%20modelling%20using%20firefly%20algorithm%20for%20phishing%20detection.pdf http://umpir.ump.edu.my/id/eprint/29847/ https://doi.org/10.25046/aj040637 https://doi.org/10.25046/aj040637 |
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| Summary: | A fuzzy system is a rule-based system that uses human experts’ knowledge to make a particular decision, while fuzzy modeling refers to the identification process of the fuzzy parameters. To generate the fuzzy parameters automatically, an optimization method is needed. One of the suitable methods provides the Firefly Algorithm (FA). FA is a nature-inspired algorithm that uses fireflies’ behavior to interpret data. This study explains in detail how fuzzy modeling works by using FA for detecting phishing. Phishing is an unsettled security problem that occurs in the world of internet connected computers. In order to experiment with the proposed method for the security threats, a database of phishing websites and SMS from different sources were used. As a result, the average accuracy for the phishing websites dataset achieved 98.86%, while the average value for the SMS dataset is 97.49%. In conclusion, both datasets show the best result in terms of the accuracy value for fuzzy modeling by using FA. |
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