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

Doctor of Philosophy in Computer Engineering

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Bibliographic Details
Main Author: Ammar Yahya, Daeef
Other Authors: R. Badlishah, Ahmad, Prof. Ir. Dr.
Format: Thesis
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2017
Subjects:
Detectors
Phishing
Network security
Phishing Detection System
Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72934
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spelling my.unimap-729342023-02-21T04:25:45Z Efficient and fast server based phishing detection system using url lexical analysis Ammar Yahya, Daeef R. Badlishah, Ahmad, Prof. Ir. Dr. Detectors Phishing Network security Phishing Detection System Doctor of Philosophy in Computer Engineering 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. 2017 2021-12-16T08:10:26Z 2021-12-16T08:10:26Z Thesis http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72934 en Universiti Malaysia Perlis (UniMAP) Universiti Malaysia Perlis (UniMAP) School of Computer and Communication Engineering
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Detectors
Phishing
Network security
Phishing Detection System
spellingShingle Detectors
Phishing
Network security
Phishing Detection System
Ammar Yahya, Daeef
Efficient and fast server based phishing detection system using url lexical analysis
description Doctor of Philosophy in Computer Engineering
author2 R. Badlishah, Ahmad, Prof. Ir. Dr.
author_facet R. Badlishah, Ahmad, Prof. Ir. Dr.
Ammar Yahya, Daeef
format Thesis
author Ammar Yahya, Daeef
author_sort Ammar Yahya, Daeef
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
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2017
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72934
_version_ 1772813063369523200
score 13.214268

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