Location-Privacy-Aware Review Publication Mechanism For Local Business Service Systems

Local business service systems (LBSS), such as Yelp and Dianping, play an essential role in making decisions like choosing a restaurant for our daily life. These systems heavily rely on individuals' voluntarily submitted reviews to build the reputation for nearby businesses. Unfortunately, the reviews expose users' private information such as visited places to the public and adversaries. Even worse, such location information is always public as it is the basic information of businesses, and adversaries could be anyone ranging from advertisement spammer to physical stalker. This paper formalizes the privacy preserving problem in local business service systems and propose a novel location privacy preserving framework. The framework can preserve users' location privacy in arbitrary local area and can maintain a good utility for both the system and every user. We evaluate our framework thoroughly towards real-world data traces. The results validate that the framework can achieve a good performance.