A hybridization of butterfly optimization algorithm and harmony search for fuzzy modelling in phishing attack detection

Fuzzy system is one of the most used systems in the decision-making and classification method as it is easy to understand because the way this system works is closer to how humans think. It is a system that uses human experts to hold the membership values to make decisions. However, it is hard to de...

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Main Authors: Noor Syahirah, Nordin, Mohd Arfian, Ismail
Format: Article
Language:English
English
Published: Springer Science and Business Media Deutschland GmbH 2023
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/40776/
http://umpir.ump.edu.my/id/eprint/40776/1/A%20hybridization%20of%20butterfly%20optimization%20algorithm%20and%20harmony.pdf
http://umpir.ump.edu.my/id/eprint/40776/2/A%20hybridization%20of%20butterfly%20optimization%20algorithm%20and%20harmony_ABS.pdf
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author Noor Syahirah, Nordin
Mohd Arfian, Ismail
author_facet Noor Syahirah, Nordin
Mohd Arfian, Ismail
author_sort Noor Syahirah, Nordin
building UMP Institutional Repository
collection Online Access
description Fuzzy system is one of the most used systems in the decision-making and classification method as it is easy to understand because the way this system works is closer to how humans think. It is a system that uses human experts to hold the membership values to make decisions. However, it is hard to determine the fuzzy parameter manually in a complex problem, and the process of generating the parameter is called fuzzy modelling. Therefore, an optimization method is needed to solve this issue, and one of the best methods to be applied is Butterfly Optimization Algorithm. In this paper, BOA was improvised by combining this algorithm with Harmony Search (HS) in order to achieve optimal results in fuzzy modelling. The advantages of both algorithms are used to balance the exploration and exploitation in the searching process. Two datasets from UCI machine learning were used: Website Phishing Dataset and Phishing Websites Dataset. As a result, the average accuracy for WPD and PWD was 98.69% and 98.80%, respectively. In conclusion, the proposed method shows promising and effective results compared to other methods.
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publisher Springer Science and Business Media Deutschland GmbH
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spelling ump-407762024-05-28T07:59:03Z http://umpir.ump.edu.my/id/eprint/40776/ A hybridization of butterfly optimization algorithm and harmony search for fuzzy modelling in phishing attack detection Noor Syahirah, Nordin Mohd Arfian, Ismail QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) Fuzzy system is one of the most used systems in the decision-making and classification method as it is easy to understand because the way this system works is closer to how humans think. It is a system that uses human experts to hold the membership values to make decisions. However, it is hard to determine the fuzzy parameter manually in a complex problem, and the process of generating the parameter is called fuzzy modelling. Therefore, an optimization method is needed to solve this issue, and one of the best methods to be applied is Butterfly Optimization Algorithm. In this paper, BOA was improvised by combining this algorithm with Harmony Search (HS) in order to achieve optimal results in fuzzy modelling. The advantages of both algorithms are used to balance the exploration and exploitation in the searching process. Two datasets from UCI machine learning were used: Website Phishing Dataset and Phishing Websites Dataset. As a result, the average accuracy for WPD and PWD was 98.69% and 98.80%, respectively. In conclusion, the proposed method shows promising and effective results compared to other methods. Springer Science and Business Media Deutschland GmbH 2023-03 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/40776/1/A%20hybridization%20of%20butterfly%20optimization%20algorithm%20and%20harmony.pdf pdf en http://umpir.ump.edu.my/id/eprint/40776/2/A%20hybridization%20of%20butterfly%20optimization%20algorithm%20and%20harmony_ABS.pdf Noor Syahirah, Nordin and Mohd Arfian, Ismail (2023) A hybridization of butterfly optimization algorithm and harmony search for fuzzy modelling in phishing attack detection. Neural Computing and Applications, 35 (7). pp. 5501-5512. ISSN 0941-0643. (Published) https://doi.org/10.1007/s00521-022-07957-0 https://doi.org/10.1007/s00521-022-07957-0
spellingShingle QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
TA Engineering (General). Civil engineering (General)
Noor Syahirah, Nordin
Mohd Arfian, Ismail
A hybridization of butterfly optimization algorithm and harmony search for fuzzy modelling in phishing attack detection
title A hybridization of butterfly optimization algorithm and harmony search for fuzzy modelling in phishing attack detection
title_full A hybridization of butterfly optimization algorithm and harmony search for fuzzy modelling in phishing attack detection
title_fullStr A hybridization of butterfly optimization algorithm and harmony search for fuzzy modelling in phishing attack detection
title_full_unstemmed A hybridization of butterfly optimization algorithm and harmony search for fuzzy modelling in phishing attack detection
title_short A hybridization of butterfly optimization algorithm and harmony search for fuzzy modelling in phishing attack detection
title_sort hybridization of butterfly optimization algorithm and harmony search for fuzzy modelling in phishing attack detection
topic QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
TA Engineering (General). Civil engineering (General)
url http://umpir.ump.edu.my/id/eprint/40776/
http://umpir.ump.edu.my/id/eprint/40776/
http://umpir.ump.edu.my/id/eprint/40776/
http://umpir.ump.edu.my/id/eprint/40776/1/A%20hybridization%20of%20butterfly%20optimization%20algorithm%20and%20harmony.pdf
http://umpir.ump.edu.my/id/eprint/40776/2/A%20hybridization%20of%20butterfly%20optimization%20algorithm%20and%20harmony_ABS.pdf