Phishing Detection Using Machine Learning Techniques
This addresses phishing detection for internet users and organizations, but it appears incremental as it compares existing methods without introducing new ones.
The paper tackled the problem of phishing website detection by comparing multiple machine learning methods to identify common characteristics in phishing attacks, but it did not report specific results or concrete numbers.
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.