A Confusion Method for the Protection of User Topic Privacy in Chinese Keyword-based Book Retrieval

Abstract

In this paper, aiming at a Chinese keyword based book search service, from a technological perspective, we propose to modify a user query sequence carefully to confuse the user query topics and thus protect the user topic privacy on the untrusted server, without compromising the accuracy of each book search service. Firstly, we propose a client-based framework for the privacy protection of book search, and then a privacy model to formulate the constraints in terms of accuracy, efficiency and security, which the cover queries generated based on a user query sequence should meet. Secondly, we present a modification algorithm for a user query sequence, based on some heuristic strategies, which can quickly generate a cover query sequence meeting the privacy model, by replacing, deleting and adding keywords for each user query. Finally, both theoretical analysis and experimental evaluation demonstrate the effectiveness of the proposed approach, i.e., which can improve the security of users’ topic privacy on the untrusted server, without compromising the efficiency, accuracy and usability of an existing Chinese keyword book search service, so it has a positive impact for the construction of a privacy-preserving text retrieval platform under an untrusted network environment.

Intelligent recommendation method of intelligent tourism scenic spot route based on collaborative filtering

“…Privacy protection in recommendations is also intuitively important, and Wu et al have made certain contributions in the area of privacy protection, such as proposing a client-based system framework for protecting user privacy and defining relevant models that can improve the security of users' topic privacy on untrusted servers [26][27][28][29][30][31].…”