Study On Semantic-Aware Location Privacy Preserving Algorithms In Road Networks

With the development of positioning technologies and the widespread use of mobile intelligent devices,LBS(Location Based Service)has brought great convenience to our daily life.Since the users need to provide accurate location information to obtain the corresponding services,it is easy for the attackers to find out the user's interests and preferences by exploiting their exposed locations,which will bring huge threats to the user's security.So,it is important to protect the user's location privacy while providing location based services.How to protect user's privacy when they are using location services is worthy of study.This paper includes an introduction of the related work of location privacy protection,discusses several kinds of location anonymous system structures,and analyzes the advantages,disadvantages and application scope of various privacy protection methods.Most of the existing privacy protection techniques do not take the semantics of the location into account,thus they are vulnerable to inference-attack based on semantic information.In order to improve the efficiency and security of the existing sematic-aware privacy preserving algorithms,we proposed two algorithms named CFSO(Circle First Structure Optimization)algorithm and AR(Attack-Resilient)algorithm.CFSO starts with the transformation from a road network to an edge-cluster graph,then adds structure-aware neighbors to the anonymous set heuristically until the set meets the user's privacy requirements,after that,replaces the user's precise location with the set.AR is based on CFSO,and it introduces controlled randomization to balance between the query performance and the vulnerability of adversary attacks.We use two real-map data sets for experiment,the experimental results show that our algorithms have a higher anonymous success rate and stronger resilience under privacy attacks,meanwhile,they are more efficient and scalable than the state-of-art techniques.