Service Selection Based on User Privacy Risk Evaluation

Abstract

Requesting a service on the Internet may require the user’s privacy data, and thus raising the risk of the user’s privacy leakage and violation. Hence, it is necessary for users to select services that protect their privacy information. However, previous studies on service selection usually focused only on the quality of service, seldom had they considered the user’s privacy concern. As such, their results may be unable to meet the user’s privacy protection requirement. Aiming at reducing the privacy risk of users in service selection, this paper proposes a fuzzy logic service selection approach. The approach uses a fuzzy model to allow a service user specifying personalized privacy preference and a service provider specifying flexible privacy requirements; then it leverages the service’s reputation, privacy policy and the user’s privacy preference to compute the privacy risk for each service candidate; finally, it ranks all service candidates based on their privacy risk degrees. Examples and evaluations show that the proposed approach is effective and efficient for reducing privacy risk in service selection.