Key Technologies Of Privacy Preservation For Location-based Services

With the ubiquity of mobile devices and the rapid development of positioning technology,a variety of applications of Location-based services(LBSs),such as POI search,vehicle navigation,location sharing,friend discovery and social game,has provided plenty of convenience for users in daily life.By collecting the sensitive information in service requests,service providers can acquire and infer the private information of users.Moreover,with the rapid expansion of the scale of users,privacy leakage is becoming more and more serious.Therefore,it is urgent to study the privacy protection of LBSs in the mobile social network.To support the privacy requirements of LBSs in mobile social network,we make the comprehensive analysis of the privacy protection of individual,the exchange and matching of privacy information and the privacy protection for collaborative groups.By integrating the theories of probability theory,information entropy,k-anonymity and similarity calculation,we focus on some key technologies of the privacy protection,in order to improve the ability of resisting attacks and balance system overheads.The major contributions of this paper are as follows:(1)A time obfuscation based privacy protection scheme,termed TOP-privacy,is proposed by researching the privacy protection of individual.TOP-privacy sends some dummy queries at leisure time to confuse the adversaries with the background information.Since the user's real query should be sent to the LBS server without making any modifications,the desired quality of service can be fully satisfied.TOP-privacy employs two important modules in terms of dummy query selection module and transmission frequency generation module.Based on the location distribution and the query distribution,the dummy query selection module selects dummy queries similar to the user's real one carefully,in order to preserve mobile user's location privacy and query privacy simultaneously.What is more,TOP-privacy updates the frequency of transmission at a fixed period,to protect a single real query effectively without revealing the movement custom of the user simultaneously.By utilizing the information entropy and normal distribution theories to establish the model,the transmission frequency generation module chooses an appropriate frequency accordingto the changes of users' movement routes.Our scheme costs less system overhead and resists against colluding attacks,inference attacks and track attacks.The scheme solves the challenges faced by a single user when he needs to protect privacy using his mobile device,and provides support for the collaborative group technology.(2)A bloom filter-based lightweight private matching scheme suitable for location-based social services,which considers common attributes and corresponding priorities,is proposed by researching the privacy match.Any two users with mobile devices can complete the privacy information matching through only one information interaction without any third party involved.The scheme exploits a two-dimensional vector similarity function based on Dice similarity coefficient,which takes into account both the number of common attributes and the corresponding priorities on each of them individually.Since the bloom filter is a space-efficient probabilistic data structure,we utilize a bloom filter to encode the set of private data for the sake of reduction of the system overhead.The confusion binary vector scalar product protocol and bloom filter-based common-attributes estimation construct lightweight private matching scheme.Our scheme does not involve time-consuming encryption operation,and resists against brute force attack and unlimited input attack.By using this scheme,users can find suitable friends close to their positions,and provide the foundation of trust among group members for collaborative group schemes.(3)On the basis of the above researches,a collaborative group scheme with incentive mechanism,termed CGS-DS,is proposed by researching the privacy protection for collaborative groups.A commonly used technique is to establish a collaborative group which helps each other to avoid privacy leakage.Due to extremely unbalanced system overhead of group members in existing such schemes,many users are short of intrinsic motivation to join the collaborative group.To address the problem,CGS-DS assigns a suitable threshold of the hop distance for each group member based on users' contributions to the collaborative group and profits from it,in order to limit mobile users consuming significant resources of collaborative group through the hop distance.Moreover,based on dummy and cache techniques,CGS-DS inspires these users to generate and cache dummies with service data for other group members to use,eventually forming a virtuous privacy protection system.Our scheme balances thesystem overhead of the group,and resists against inference attacks and center of cloaking area attacks.