Efficient and fast server based phishing detection system using url lexical analysis

Phishing attack detection is a significant research area for network security applications. Legitimate websites is typically prone to phishing attacks. Phishing poses an ongoing challenge and continues to be a threat via numerous vectors such as search engines, fake websites, emails and instant mess...

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Format:	Thesis
Language:	English
Subjects:	Detectors Phishing Network security Phishing Detection System
Online Access:	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72934/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72934/2/Full%20text.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72934/5/Ammar%20Yahya.pdf
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spelling	my-unimap-729342023-02-21T04:25:45Z Efficient and fast server based phishing detection system using url lexical analysis R. Badlishah, Ahmad, Prof. Ir. Dr. Phishing attack detection is a significant research area for network security applications. Legitimate websites is typically prone to phishing attacks. Phishing poses an ongoing challenge and continues to be a threat via numerous vectors such as search engines, fake websites, emails and instant messages. It has evolved its deceptions to remain one step ahead of the latest countermeasures. It exploits the weaknesses of the users which makes solving this problem especially complex. Phishing classifier uses the extracted features to detect the phishing websites and it depends on either the website’s content, the Uniform Resource Locator (URL) or both of them. The URL feature extraction comprises host and lexical information. In this thesis, the feature extraction is based on the lexical features only in order to reduce the processing overhead due to the host information feature extraction. These features are utilized by a classifier to detect the phishing website. Most of the phishing attack detection strategies served the client side detection mechanisms. In this thesis, a new server side phishing attack detection technique is proposed to achieve fast, robust and accurate system by using lexical features alone. The first part of thesis presents analysis and development for the existing lexical features of URL including the tokenization and n-gram mechanisms which extract and analyze tokens and n-gram distribution of legitimate and phishing datasets followed by implementing Token based Classifier (TCL) and N-gram based Classifier (NGCL). Therefore, TCL and NGCL segment URLs into tokens and n-grams respectively and employ their distribution for classification process. Also, the first part of thesis proposing Language Model based Classifier (LMCL) which build a model for both of phishing and legitimate classes to classify URLs according to the highest probability and compared with TCL and NGCL classifiers. Universiti Malaysia Perlis (UniMAP) Thesis en http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72934 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72934/4/license.txt 8a4605be74aa9ea9d79846c1fba20a33 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72934/1/Page%201-24.pdf 560eaf92178527d5fb06465056409098 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72934/2/Full%20text.pdf f909905efad04856444974a022ad41f1 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72934/5/Ammar%20Yahya.pdf 867190d23f00ae9e6abea16733bd0269 Universiti Malaysia Perlis (UniMAP) Detectors Phishing Network security Phishing Detection System School of Computer and Communication Engineering
institution	Universiti Malaysia Perlis
collection	UniMAP Institutional Repository
language	English
advisor	R. Badlishah, Ahmad, Prof. Ir. Dr.
topic	Detectors Phishing Network security Phishing Detection System
spellingShingle	Detectors Phishing Network security Phishing Detection System Efficient and fast server based phishing detection system using url lexical analysis
description	Phishing attack detection is a significant research area for network security applications. Legitimate websites is typically prone to phishing attacks. Phishing poses an ongoing challenge and continues to be a threat via numerous vectors such as search engines, fake websites, emails and instant messages. It has evolved its deceptions to remain one step ahead of the latest countermeasures. It exploits the weaknesses of the users which makes solving this problem especially complex. Phishing classifier uses the extracted features to detect the phishing websites and it depends on either the website’s content, the Uniform Resource Locator (URL) or both of them. The URL feature extraction comprises host and lexical information. In this thesis, the feature extraction is based on the lexical features only in order to reduce the processing overhead due to the host information feature extraction. These features are utilized by a classifier to detect the phishing website. Most of the phishing attack detection strategies served the client side detection mechanisms. In this thesis, a new server side phishing attack detection technique is proposed to achieve fast, robust and accurate system by using lexical features alone. The first part of thesis presents analysis and development for the existing lexical features of URL including the tokenization and n-gram mechanisms which extract and analyze tokens and n-gram distribution of legitimate and phishing datasets followed by implementing Token based Classifier (TCL) and N-gram based Classifier (NGCL). Therefore, TCL and NGCL segment URLs into tokens and n-grams respectively and employ their distribution for classification process. Also, the first part of thesis proposing Language Model based Classifier (LMCL) which build a model for both of phishing and legitimate classes to classify URLs according to the highest probability and compared with TCL and NGCL classifiers.
format	Thesis
title	Efficient and fast server based phishing detection system using url lexical analysis
title_short	Efficient and fast server based phishing detection system using url lexical analysis
title_full	Efficient and fast server based phishing detection system using url lexical analysis
title_fullStr	Efficient and fast server based phishing detection system using url lexical analysis
title_full_unstemmed	Efficient and fast server based phishing detection system using url lexical analysis
title_sort	efficient and fast server based phishing detection system using url lexical analysis
granting_institution	Universiti Malaysia Perlis (UniMAP)
granting_department	School of Computer and Communication Engineering
url	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72934/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72934/2/Full%20text.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72934/5/Ammar%20Yahya.pdf
_version_	1776104229423808512

Efficient and fast server based phishing detection system using url lexical analysis

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