An improved method using fuzzy system based on hybrid boahs for phishing attack detection

A fuzzy system is a rule-based system that uses human expert's knowledge which holds the truth or false values to make a particular decision. However, it is difficult to generate fuzzy parameters manually to classify data when it comes to a very complex problem. Therefore, metaheuristic algorit...

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Main Author:	Noor Syahirah, Nordin
Format:	Thesis
Language:	English
Published:	2022
Subjects:	Q Science (General)
Online Access:	http://umpir.ump.edu.my/id/eprint/37654/1/ir.An%20improved%20method%20using%20fuzzy%20system%20based%20on%20hybrid%20boahs%20for%20phishing%20attack%20detection.pdf
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spelling	my-ump-ir.376542023-09-18T03:37:05Z An improved method using fuzzy system based on hybrid boahs for phishing attack detection 2022-03 Noor Syahirah, Nordin Q Science (General) QA75 Electronic computers. Computer science A fuzzy system is a rule-based system that uses human expert's knowledge which holds the truth or false values to make a particular decision. However, it is difficult to generate fuzzy parameters manually to classify data when it comes to a very complex problem. Therefore, metaheuristic algorithm as the optimization method is needed to solve this issue. A small experiment was being performed to choose the best metaheuristic algorithm where seven metaheuristic algorithms were analyzed in terms of their performance measurement that including accuracy, recall, precision, and f-measure. The algorithms involved were Genetic Algorithm, Differential Evolution Algorithm, Particle Swarm Optimization, Butterfly Optimization Algorithm, Teaching-Learning-Based Optimization Algorithm, Harmony Search Algorithm and Gravitational Search Algorithm. The proposed method of this study is to cater the problems occur in fuzzy systems by using optimization method. Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. The proposed algorithm has utilized the advantages of both algorithms to balance the exploration and exploitation search process. The experiment was executed by using k-fold cross validation techniques for predicting the classification algorithm performance. Thereby, two datasets; Website Phishing Dataset and Phishing Websites Dataset were used to test the performance of the proposed method. As a result, the average accuracy value for both datasets are 98.69% and 98.80% respectively. The proposed method has proven to outperform the other methods including the standard BOA and HS algorithm. 2022-03 Thesis http://umpir.ump.edu.my/id/eprint/37654/ http://umpir.ump.edu.my/id/eprint/37654/1/ir.An%20improved%20method%20using%20fuzzy%20system%20based%20on%20hybrid%20boahs%20for%20phishing%20attack%20detection.pdf pdf en public masters Universiti Malaysia Pahang Faculty of Computing Mohd Arfian, Ismail
institution	Universiti Malaysia Pahang Al-Sultan Abdullah
collection	UMPSA Institutional Repository
language	English
advisor	Mohd Arfian, Ismail
topic	Q Science (General) Q Science (General)
spellingShingle	Q Science (General) Q Science (General) Noor Syahirah, Nordin An improved method using fuzzy system based on hybrid boahs for phishing attack detection
description	A fuzzy system is a rule-based system that uses human expert's knowledge which holds the truth or false values to make a particular decision. However, it is difficult to generate fuzzy parameters manually to classify data when it comes to a very complex problem. Therefore, metaheuristic algorithm as the optimization method is needed to solve this issue. A small experiment was being performed to choose the best metaheuristic algorithm where seven metaheuristic algorithms were analyzed in terms of their performance measurement that including accuracy, recall, precision, and f-measure. The algorithms involved were Genetic Algorithm, Differential Evolution Algorithm, Particle Swarm Optimization, Butterfly Optimization Algorithm, Teaching-Learning-Based Optimization Algorithm, Harmony Search Algorithm and Gravitational Search Algorithm. The proposed method of this study is to cater the problems occur in fuzzy systems by using optimization method. Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. The proposed algorithm has utilized the advantages of both algorithms to balance the exploration and exploitation search process. The experiment was executed by using k-fold cross validation techniques for predicting the classification algorithm performance. Thereby, two datasets; Website Phishing Dataset and Phishing Websites Dataset were used to test the performance of the proposed method. As a result, the average accuracy value for both datasets are 98.69% and 98.80% respectively. The proposed method has proven to outperform the other methods including the standard BOA and HS algorithm.
format	Thesis
qualification_level	Master's degree
author	Noor Syahirah, Nordin
author_facet	Noor Syahirah, Nordin
author_sort	Noor Syahirah, Nordin
title	An improved method using fuzzy system based on hybrid boahs for phishing attack detection
title_short	An improved method using fuzzy system based on hybrid boahs for phishing attack detection
title_full	An improved method using fuzzy system based on hybrid boahs for phishing attack detection
title_fullStr	An improved method using fuzzy system based on hybrid boahs for phishing attack detection
title_full_unstemmed	An improved method using fuzzy system based on hybrid boahs for phishing attack detection
title_sort	improved method using fuzzy system based on hybrid boahs for phishing attack detection
granting_institution	Universiti Malaysia Pahang
granting_department	Faculty of Computing
publishDate	2022
url	http://umpir.ump.edu.my/id/eprint/37654/1/ir.An%20improved%20method%20using%20fuzzy%20system%20based%20on%20hybrid%20boahs%20for%20phishing%20attack%20detection.pdf
_version_	1783732274466914304

An improved method using fuzzy system based on hybrid boahs for phishing attack detection

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