Algorithm to trade off between utility and privacy cost of online social search

Abstract

Online social search such as Quora and Zhihu brings new ways to obtain answers to questions in social networks. However, personal and other sensitive information may be exposed to others when the question spreads via the social network. People obtain utility when they obtain answers to their questions but may suffer privacy cost when their personal information is known by others. Researchers are seeking methods and tools to help users get utility and protect their privacy at the same time. In this paper, we study this problem by proposing a framework to quantitatively evaluate the utility and privacy cost in online social search. Besides, we design an algorithm under our framework to help users trade off their utility and privacy cost. Simulations are performed to illustrate the concepts in our framework and demonstrate the advantages of our algorithm. © 2016 IEEE.