Journal of Network and Information Security

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Effectiveness of Machine Learning Techniques in Phishing Detection


Affiliations
1 Computer Engineering Department, Sharif University of Technology, Tehran, Iran, Islamic Republic of
2 School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran, Islamic Republic of
     

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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.

Keywords

Classification, Cybercrime, Machine-learning, Phishing.
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  • Effectiveness of Machine Learning Techniques in Phishing Detection

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Authors

Vahid Shahrivari
Computer Engineering Department, Sharif University of Technology, Tehran, Iran, Islamic Republic of
Mohammad Izadi
Computer Engineering Department, Sharif University of Technology, Tehran, Iran, Islamic Republic of
Mohammad Mahdi Darabi
School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran, Islamic Republic of

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.

Keywords


Classification, Cybercrime, Machine-learning, Phishing.

References