Visible to the public Phishing Detection and Prevention using Chrome Extension

TitlePhishing Detection and Prevention using Chrome Extension
Publication TypeConference Paper
Year of Publication2022
AuthorsSyafiq Rohmat Rose, M. Amir, Basir, Nurlida, Nabila Rafie Heng, Nur Fatin, Juana Mohd Zaizi, Nurzi, Saudi, Madihah Mohd
Conference Name2022 10th International Symposium on Digital Forensics and Security (ISDFS)
Date Publishedjun
KeywordsAdaptation models, Chrome Extension, Human Behavior, machine learning, machine learning algorithms, phishing, pubcrawl, supervised learning, support vector machine, Support vector machines, URL-based features, web services
AbstractDuring pandemic COVID-19 outbreaks, number of cyber-attacks including phishing activities have increased tremendously. Nowadays many technical solutions on phishing detection were developed, however these approaches were either unsuccessful or unable to identify phishing pages and detect malicious codes efficiently. One of the downside is due to poor detection accuracy and low adaptability to new phishing connections. Another reason behind the unsuccessful anti-phishing solutions is an arbitrary selected URL-based classification features which may produce false results to the detection. Therefore, in this work, an intelligent phishing detection and prevention model is designed. The proposed model employs a self-destruct detection algorithm in which, machine learning, especially supervised learning algorithm was used. All employed rules in algorithm will focus on URL-based web characteristic, which attackers rely upon to redirect the victims to the simulated sites. A dataset from various sources such as Phish Tank and UCI Machine Learning repository were used and the testing was conducted in a controlled lab environment. As a result, a chrome extension phishing detection were developed based on the proposed model to help in preventing phishing attacks with an appropriate countermeasure and keep users aware of phishing while visiting illegitimate websites. It is believed that this smart phishing detection and prevention model able to prevent fraud and spam websites and lessen the cyber-crime and cyber-crisis that arise from year to year.
DOI10.1109/ISDFS55398.2022.9800826
Citation Keysyafiq_rohmat_rose_phishing_2022