Achieving User-Defined Location Privacy Preservation Using a P2P System

Abstract

As location-based services become widely used in daily life, there is growing concern in preserving location privacy of users to avoid that attackers infer information about users by collecting and analyzing requests initiated by users. We argue that a good location privacy preservation scheme should have these properties. First, a user should never expose its precise location to any other entity. Second, a user should be able to specify its own requirement on the strength of privacy preservation, since a stricter preservation requirement may increase its overhead. Third, the scheme should be able to preserve as many as possible aspects of users' privacy under various attacks. With these desired properties in mind, we carefully design an encoding scheme of users' identifiers and a fully distributed architecture for our purpose and propose a privacy preservation scheme based on them. With the help of the encoding scheme and the distributed architecture, we develop a distributed negotiation algorithm to help users conduct negotiations among themselves to find their cloaked regions that satisfy their self-defined requirements without exposing their precise locations. The negotiations are completed without coordination from any central servers, and a random proxy is selected for each individual request, therefore the potential risks caused by any central server (location-based service servers or trusted-third-party servers) are mitigated as much as possible. Experiments show that our scheme can satisfy different strengths of privacy preservation required by each user even under the most severe scenarios.

A Vehicle Trajectory Privacy Preservation Method Based on Caching and Dummy Locations in the Internet of Vehicles

“…Hence, it is difficult to obtain the trajectory of a vehicle user through LCA. Next, we will prove these analyses through simulation compared with the K-anonymity method [34] and dummy location-based method [45].…”

“…The problem of location privacy preservation has been attracting wide attention from both academia and industry, and this problem draws even more attention due to the booming of LBSs. Up to now, many location privacy preservation methods have been proposed, including K-anonymity-based method [33][34][35][36], obfuscation-based method [37][38][39], differential privacy-based method [40,41], homomorphic encryption-based method [42][43][44] and dummy location-based method [6][7][8][9][10][11][12][13]45]. In this work, we focus on the trajectory privacy preservation method based on dummy locations in IoVs.…”

An Enhanced Location Scattering Based Privacy Protection Scheme

“…Another decentralized pri-vacy protection approach is introduced in [15] that allows the nodes to cache POIs data in which they are located in and serves the neighboring queries. A fully distributed architecture is proposed in [16] that allow the user to specify their privacy requirements and to find their cloaking regions without revealing their precise locations. The major limitation of collaboration-based approaches is that mobile devices must have powerful computational capabilities.…”

A Location Privacy Preservation Method Based on Dummy Locations in Internet of Vehicles

“…This problem draws even more attention due to the booming of LBSs. Many location privacy-preservation methods have been proposed, such as Kanonymity [7][8][9][10], obfuscation [11][12][13], differential privacy [26,27], mixed zone [28,29], homomorphic encryption [30][31][32], and dummy locations [15][16][17][18][19][20][21][22][23]. In this work, we focus on the location privacy preservation-method based on dummy locations in IoV.…”

“…However, K-anonymity privacy-preserving scheme is suitable for high vehicle density. When there are fewer vehicles, spatial anonymity may not be realized, or the anonymous area formed is too large [9]. On the other hand, for the point of interest (POI) retrieval service in IoV, the accuracy of retrieval results is related to the precision of provided location information.…”