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      Phishing Detection Using Machine Learning Techniques

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          Abstract

          The Internet has become an indispensable part of our life, However, It also has provided opportunities to anonymously perform malicious activities like Phishing. Phishers try to deceive their victims by social engineering or creating mock-up websites to steal information such as account ID, username, password from individuals and organizations. Although many methods have been proposed to detect phishing websites, Phishers have evolved their methods to escape from these detection methods. One of the most successful methods for detecting these malicious activities is Machine Learning. This is because most Phishing attacks have some common characteristics which can be identified by machine learning methods. In this paper, we compared the results of multiple machine learning methods for predicting phishing websites.

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          Author and article information

          Journal
          20 September 2020
          Article
          2009.11116
          d780bb58-57f1-4d04-b15b-6146be823c33

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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          Custom metadata
          cs.CR cs.AI cs.LG stat.ML

          Security & Cryptology,Machine learning,Artificial intelligence
          Security & Cryptology, Machine learning, Artificial intelligence

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