Anti-phishing based on automated individual white-list

In phishing and pharming, users could be easily tricked into submitting their username/passwords into fraudulent web sites whose appearances look similar as the genuine ones. The traditional blacklist approach for anti-phishing is partially effective due to its partial list of global phishing sites. In this paper, we present a novel anti-phishing approach named Automated Individual White-List (AIWL). AIWL automatically tries to maintain a white-list of user’s all familiar Login User Interfaces (LUIs) of web sites. Once a user tries to submit his/her confidential information to an LUI that is not in the white-list, AIWL will alert the user to the possible attack. Next, AIWL can efficiently defend against pharming attacks, because AIWL will alert the user when the legitimate IP is maliciously changed; the legitimate IP addresses, as one of the contents of LUI, are recorded in the white-list and our experiment shows that popular web sites’ IP addresses are basically stable. Furthermo...

• Type: Conference
• Year: 2008
• Where: DIM
• Authors: Ye Cao, Weili Han, Yueran Le
• Keywords: DIM 2008, Information Technology, Login User Interface, Naive Bayesian Classifier, Web Sites