Phishing Websites Detection Using Machine Learning
R. Kiruthiga1, D. Akila2

1R. Kiruthiga, Ph.D, Research Scholar, Department of Computer Science, VELS Institute of Science, Technology & Advanced Studies, Chennai (Tamil Nadu), India.
2Dr. D. Akila, Associate Professor, Department of Information Technology, VELS Institute of Science, Technology & Advanced Studies, Chennai (Tamil Nadu), India.
Manuscript received on 10 October 2019 | Revised Manuscript received on 19 October 2019 | Manuscript Published on 02 November 2019 | PP: 111-114 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B10180982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1018.0982S1119
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Abstract: Phishing is a common attack on credulous people by making them to disclose their unique information using counterfeit websites. The objective of phishing website URLs is to purloin the personal information like user name, passwords and online banking transactions. Phishers use the websites which are visually and semantically similar to those real websites. As technology continues to grow, phishing techniques started to progress rapidly and this needs to be prevented by using anti-phishing mechanisms to detect phishing. Machine learning is a powerful tool used to strive against phishing attacks. This paper surveys the features used for detection and detection techniques using machine learning.
Keywords: Phishing, Phishing Websites, Detection, Machine Learning.
Scope of the Article: Machine Learning