Promoting Privacy Protection, in Customized Web Search with Anchored User Profile

P. Hena Monica Anand, S. Radha Krishna

Abstract: Web search engines are widely used to find certain data among a huge amount of information in a nominal amount of time. We can implement the String Matching KMP Algorithm for improving the better search quality results. To come up with this privacy threat, present solutions introduce new mechanisms that precede a high cost in terms of computation and communication. Personalized search is a promising means to obtain better accuracy of web search, and has been attracting more attention lately. Nevertheless, effective, personalized search needs collecting and aggregating user data, which often increases serious concerns of privacy infringement for many users. Indeed, these businesses have become one of the main barriers for deploying personalized search applications, and how to do privacy-preserving personalization is a big challenge. In this, we introduce and attempt to resist adversaries with more extensive background knowledge, such as richer relationship amongst topics. Richer relationship means we generalize the user profile results by applying the background knowledge which is starting to save in history. Through this, we can hide the user search results. By applying this mechanism, we can achieve the privacy.

Keywords: Privacy protection, PWS, risk, String Matching KMP