A Computer Vision Technique to Detect Phishing Attacks

Abstract

Phishing refers to cybercrime that use social engineering and technical subterfuge techniques to fool online users into revealing sensitive information such as username, password, bank account number or social security number. In this paper, we propose a novel solution to defend zero-day phishing attacks. Our proposed approach is a combination of white list and visual similarity based techniques. We use computer vision technique called SURF detector to extract discriminative key point features from both suspicious and targeted websites. Then they are used for computing similarity degree between the legitimate and suspicious pages. Our proposed solution is efficient, covers a wide range of websites phishing attacks and results in less false positive rate.