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LARX: Large-Scale Anti-Phishing by Retrospective Data-Exploring Based on a Cloud Computing Platform

Anti-phishing is an intriguing challenge for Internet users especially for online business or e-pay users. Tracking phishing is quite difficult because most victims are not instantly aware of phishing attacks until their accounts are compromised, and monetary losses occur. Most web browsers provide plug-ins to protect users from phishing websites, but a client side solution cannot provide detailed forensic information on phishing attacks. In this paper, we propose an offline phishing detection system named LARX (acronym for Large-scale Anti-phishing by Retrospective data-eXploration). LARX uses network traffic data archived at a vantage point and analyzes these data for phishing attacks. All of LARX's phishing filtering operations use cloud computing platforms and work in parallel. As an off-line solution for phishing attack detection, LARX can be effectively scaled up to analyze a large volume of trace data when enough computing power and storage capacity are provided.