Countering Phishing from Brands' Vantage Point
Title | Countering Phishing from Brands' Vantage Point |
Publication Type | Conference Paper |
Year of Publication | 2016 |
Authors | Bulakh, Vlad, Gupta, Minaxi |
Conference Name | Proceedings of the 2016 ACM on International Workshop on Security And Privacy Analytics |
Publisher | ACM |
Conference Location | New York, NY, USA |
ISBN Number | 978-1-4503-4077-9 |
Keywords | AdaBoost, classifier, Human Behavior, machine learning, phishing, phishing attack, pubcrawl, Random Forest, supervised machine learning |
Abstract | 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. |
URL | http://doi.acm.org/10.1145/2875475.2875478 |
DOI | 10.1145/2875475.2875478 |
Citation Key | bulakh_countering_2016 |