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: Noor Syahirah, Nordin, Mohd Arfian, Ismail, Mezhuyev, Vitaliy, Shahreen, Kasim, Mohd Saberi, Mohamad, Ashraf Osman, Ibrahim
Format: Article
Language:English
Published: ASTES Publishers 2019
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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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Institution: Universiti Malaysia Pahang
Language: English
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spelling my.ump.umpir.298472020-11-13T07:01:03Z http://umpir.ump.edu.my/id/eprint/29847/ Fuzzy modelling using firefly algorithm for phishing detection Noor Syahirah, Nordin Mohd Arfian, Ismail Mezhuyev, Vitaliy Shahreen, Kasim Mohd Saberi, Mohamad Ashraf Osman, Ibrahim QA76 Computer software T Technology (General) 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. ASTES Publishers 2019-12-12 Article PeerReviewed pdf en cc_by_sa_4 http://umpir.ump.edu.my/id/eprint/29847/1/Fuzzy%20modelling%20using%20firefly%20algorithm%20for%20phishing%20detection.pdf Noor Syahirah, Nordin and Mohd Arfian, Ismail and Mezhuyev, Vitaliy and Shahreen, Kasim and Mohd Saberi, Mohamad and Ashraf Osman, Ibrahim (2019) Fuzzy modelling using firefly algorithm for phishing detection. Advances in Science, Technology and Engineering Systems Journal, 4 (6). pp. 291-296. ISSN 2415-6698 https://doi.org/10.25046/aj040637 https://doi.org/10.25046/aj040637
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QA76 Computer software
T Technology (General)
spellingShingle QA76 Computer software
T Technology (General)
Noor Syahirah, Nordin
Mohd Arfian, Ismail
Mezhuyev, Vitaliy
Shahreen, Kasim
Mohd Saberi, Mohamad
Ashraf Osman, Ibrahim
Fuzzy modelling using firefly algorithm for phishing detection
description 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.
format Article
author Noor Syahirah, Nordin
Mohd Arfian, Ismail
Mezhuyev, Vitaliy
Shahreen, Kasim
Mohd Saberi, Mohamad
Ashraf Osman, Ibrahim
author_facet Noor Syahirah, Nordin
Mohd Arfian, Ismail
Mezhuyev, Vitaliy
Shahreen, Kasim
Mohd Saberi, Mohamad
Ashraf Osman, Ibrahim
author_sort Noor Syahirah, Nordin
title Fuzzy modelling using firefly algorithm for phishing detection
title_short Fuzzy modelling using firefly algorithm for phishing detection
title_full Fuzzy modelling using firefly algorithm for phishing detection
title_fullStr Fuzzy modelling using firefly algorithm for phishing detection
title_full_unstemmed Fuzzy modelling using firefly algorithm for phishing detection
title_sort fuzzy modelling using firefly algorithm for phishing detection
publisher ASTES Publishers
publishDate 2019
url 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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