Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6900241 | Procedia Computer Science | 2018 | 7 Pages |
Abstract
Phishing websites are typical starting points of online social engineering attacks, including many recent online scams. The attackers develop web pages mimicking legitimate websites, and send the malicious URLs to victims to lure them to input their sensitive information. Existing phishing defense mechanisms are not sufficient to detect with new phishing attacks. In this paper, we aim to improve phishing detection techniques using machine learning techniques. In particular, we propose a learning-based aggregation analysis mechanism to decide page layout similarity, which is used to detect phishing pages. Our experiment results shows that our approach is accurate and effective in detecting phishing pages.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Jian Mao, Jingdong Bian, Wenqian Tian, Shishi Zhu, Tao Wei, Aili Li, Zhenkai Liang,