Developing an efficient fuzzy model for phishing identification

The explosive growth of Internet commerce has made phishers who may attempt to create phishing sites aimed to steal personal information such as password, banking account and credit card account details, etc. Most of these phishing pages look similar to the real pages in terms of interface and uniform resource locator (URL) address. Many techniques have been proposed to identify phishing sites. However, the numbers of victims have been increasing due to inefficient protection technique. In this paper, we develop a fuzzy model for phishing identification efficiently. The model eliminates the subjective factors to improve efficiency such as if-then rule sets, the parameters of membership functions, etc. Moreover, the efficiency features for identifying phishing were used for the fuzzy model. The proposed technique is evaluated with the datasets of 11,660 phishing sites and 5,000 legitimate sites. The results show that the proposed technique can identify over 99% phishing sites.