An Incentive Mechanism For K-Anonymity Location Privacy Based On Local Storage Of Reputation

With the explosion of the mobile electronic devices with location-based sevices and the rapid development of the location technology with GPS and the base station, LBS(location based service) is becoming more and more popular. However, with the convenience taken by the widely used of this technology, our privacy and other information about the location are suffering unprecedented threats. Such as when users query a nearby hospital several times, they might reveal their health status.To deal with these challenges, scholars have done many researches on privacy protection for location based services. Now existing techniques ignore the problem that not all mobile users are willing to participate in the anonymity set. This leads to them not available actually. In response to these problems, the author ’s major contributions are as follows:1. This paper introduces incentive mechanism into k-anonymity location privacy, design a model and achieve the related protocol. Based on the distributed K-anonymity, the reputation is stored in the certificates locally in the peers. Users gain and accumulate reputation by providing anonymous services to their neighbors. By introducing the semi-trusted third part, the cloud, the integrity of the locally stored reputation is ensured. During the trade, users have to reach a certain threshold in order to obtain anonymous service. By this way, we achieve the purpose of incentive.2. Analysis shows that the proposed scheme can resist camouflage, replay, collusion and other typical attacks, it also has the ability to avoid free-riding behavior. Comparing with the only one K-anonymity incentive scheme, the proposed scheme takes user’s history behavior into account, the incentive effect is more significant and have continuity, and our scheme does not require the help of a trusted third party, avoiding the bottlenecks and security issues.3. We build a wireless network environment test bed, and implement the proposed K-anonymity incentive mechanism. Lots of experiments show that: the time consummed by the proposed scheme to generate the anonymous area is little, and it hasa very slow growth in the number of users increases, the additional traffic introduced is few.