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A Proactive Approach to Predict Phishing Websites

Prabhakar, Keerthi (2021) A Proactive Approach to Predict Phishing Websites. Masters thesis, Dublin, National College of Ireland.

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Among Cyber-attacks, Phishing is the most prevailing attack that deceit users to provide sensitive data like credentials, bank and financial details which later wields to loss of funds. Although there are several sources like text messages, voice calls, typically, e-mails are the main source to target naive users. Prototypical users are misled by the attackers who create an exact duplicate of a legitimate website however making it malicious. As a result, it is paramount to efficiently detect and eliminate this attack. The fundamental focus of this experiment is to predict the URLs that are not genuine, and to make users informed of such social engineering attempts. This study mainly deals with the extraction of relevant features of URL to detect the unsafe links that are a copy of authentic web pages. An ensemble model is developed employing Deep learning (DL) approaches and Machine learning (ML) techniques to foresee the authenticity of the URL. This study has developed an optimal model that has achieved an accuracy of 99.1% for the Random Forest classifier.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Q Science > QA Mathematics > Computer software > Computer Security
T Technology > T Technology (General) > Information Technology > Computer software > Computer Security
Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions: School of Computing > Master of Science in Cyber Security
Depositing User: Tamara Malone
Date Deposited: 29 Dec 2022 12:59
Last Modified: 07 Mar 2023 12:32

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