Phishing Detection Using Machine Learning

Phishing Detection Using Machine Learning

Dr. Vijay. B. More, Gauri Vishal Desale, Tejashree Subhash Agrahari, Darshan Ramdas Desale, Revati Pitambar Jagtap

Department of Computer Science

Met, Institute of Engineering

Abstract - The exponential increase in phishing assaults has led to significant financial losses for both individuals and companies, and it has also raised questions regarding the security and privacy of their personal information. The notable annual increase in phishing attempts suggests that the existing detection methods are inadequate, underscoring the need for the development of more robust and effective phishing detection techniques. This paper introduces an extension model for phishing detection employing machine learning, with the aim of enhancing both efficacy and accuracy in identifying phishing attempts. The survey conducted in this paper delves into the current state-of-the-art techniques in phishing detection, highlighting their limitations. Furthermore, it puts forth a novel approach in the developmental stages, centered around feature extraction from malicious URLs using machine learning.

Key Words:  Machine Learning, Phishing Detection Extension,