Phising Attacks Prevention Using Web Cache Optimization

Abstract

Phishing is an emerging type of social engineering crime on the Web. Most phishers initiate attacks by sending emails to potential victims. These emails lure users to access fake websites, and induce them to expose sensitive and/or private information. The rapid development and evolution of phishing techniques pose a big challenge in Web identity security for computer science researchers in both academia and industry. All phishing attacks spoof users from the visual level and semantic level, i.e., they make the appearances of web pages look similar to the real ones and make the web links and web page contents semantically related to the real ones. In this work, we evaluate visual features that are completely from the computer screen. After the fake page is got through web cache, we check each cache file in the cache directory through phishing. Caching is a technique first used by memory management to reduce bus traffic and latency of data access. With the significant increase of Web traffic, caching techniques are applied to Web caching to reduce network traffic, user-perceived latency, and server load by caching the documents in local proxies. In this work, analization of both advantages and disadvantages of some current Web cache replacement algorithms including lowest relative value algorithm, least weighted usage algorithm and least unified-value (LUV) algorithm is done. Based on our analysis, we proposed a new algorithm, called least grade replacement (LGR), which takes recency, frequency, perfect-history, and document size into account for Web cache optimization..We use web caching techniques to assess the visual features’ similarity. We further convert the retrieved web pages into images and use EMD to calculate their similarity to the protected web pages. Our experiments show that this method is superior to all other visual assessment methods.