Visible to the public Countering Phishing from Brands' Vantage Point

TitleCountering Phishing from Brands' Vantage Point
Publication TypeConference Paper
Year of Publication2016
AuthorsBulakh, Vlad, Gupta, Minaxi
Conference NameProceedings of the 2016 ACM on International Workshop on Security And Privacy Analytics
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-4077-9
KeywordsAdaBoost, classifier, Human Behavior, machine learning, phishing, phishing attack, pubcrawl, Random Forest, supervised machine learning

Most anti-phishing solutions that exist today require scanning a large portion of the web, which is vast and equivalent to finding a needle in a haystack. In addition, such solutions are not very efficient. We propose a different approach. Our solution does not rely on the scanning of the entire Internet or a large portion of it and only needs access to the brand's traffic in order to be able to detect phishing attempts against that brand. By analyzing a sample of phishing websites, we find features that can be used to distinguish phishing websites from the legitimate ones. We then use these features to train a machine learning classifier capable of helping brands detect phishing attempts against them. Our approach can detect up to 86% of phishing attacks against the brands and is best used as a complementary tool to the existing anti-phishing solutions.

Citation Keybulakh_countering_2016