Global and Personalized Query Probability for Obfuscation-Based Web Search

Over the past few years, the volumes of digital information have increased dramatically. Web search engines become indispensable to our daily lives due to their capability of filtering relevant information. The web search engines collect users' online behavior data which implies their personalized interest, even contains sensitive information. A malicious attacker may benefit from advertising or manipulating political campaigns, which poses a serious threat to public security. In this paper, we propose two new methods to generate dummy queries base on global and personalized queries' probability. The generated anonymous queries set has greater information entropy which helps to protect user's intent in web search. Experiment results verify the validity of our methods.