Date of Award
Master of Science
Electrical and Computer Engineering
Most known anti-phishing tools are based in “black-list” system and http headers, but some phishing sites have been used web cloaking technique to avoid possible detection. These kinds pf phishing websites have an officially and trustful web content at ordinary times but triggered by some specific keyword on search engines. Contrapose this phenomenon, a new method based on anonymous, distributed and active probing-based for detecting cloaking fast-flux phishing websites is presented. This research works on 5 of top 10 world Search engines, which are Bing, Ask, Aol, Lycos and Search. We have two models to detect phishing website. Model A based on local dictionary, search random keywords through all search engines to detect suspicious website; Model B will determine specific URLs whether suspicious or not by our detection system.
Guo, Ziji, "World-wide cloaking phishing websites detection" (2017). Graduate Theses and Dissertations. 16365.