Research On Privacy Protection Methods For Location-based Services

For the past few years,with the rapid development of mobile communication technology and mobile positioning technology,as well as the widespread of mobile devices such as smart phones and smart watches,location-based services have been widely used and have covered all aspects of people's daily life.However,while location-based services bring such great convenience to people,they also bring some risks of location privacy leakage.When using location-based services,users need to send the current location information to location service provider.If the location information is abused by the location service provider or stolen by a third-party malicious attacker,the user's personal privacy will be exposed.By statistics and analysis of a user's location information,they can infer the user's sensitive personal information,such as home address,company address,income level,interests,hobbies,and movement trajectory.Therefore,how to protect users' privacy has become a key issue to be solved urgently for the sustainable and healthy development of location-based services.However,the existing privacy protection methods of location-based services can not meet the increasingly rich location-based services scenarios for the intensity of privacy protection and service quality requirements.Therefore,this thesis makes an in-depth study of privacy protection in two scenarios,location-based information query service and location-based ridesharing matching service,and proposes two efficient and practical privacy protection methods for location-based services.The specific work and contributions are as follows:(1)To protect privacy of users in location-based information query service,a privacy protection technology of information query service that supports spatio-temporal keywords is proposed.This technology supports users to perform spatial and temporal ranges and Boolean keyword query on encrypted LBS data stored in the cloud.In order to protect the privacy of users' queries and the confidentiality of cloud data,this technology uses the secure k-nearest neighbor algorithm and Euclidean distance to realize the privacy protection of the spatial range query,uses the bilinear pair theory and the 0 coding and 1 coding technology to realize the privacy protection of the temporal range query,and uses the key policy attribute-based encryption algorithm realizes privacy protection for Boolean keyword query.On this basis,in order to further improve the search efficiency of the cloud,the technology is based on Geohash technology to design a grid computing algorithm with a tree index structure,which significantly reduces the cloud search overhead.Security analysis and experimental simulation results show that the technology can effectively protect the query privacy of users and the confidentiality of LBS data,and is very practical and efficient.(2)To protect the user's privacy in the location-based ridesharing matching service,a location-based dynamic ridesharing matching privacy protection mechanism is proposed.This mechanism supports the ridesharing service provider according to the rider's ridesharing request and the driver's location information and schedule to select a driver who can serve a rider with minimal additional travel distance,and the location privacy of both the drivers and riders are protected.Different from the existing privacy protection mechanism based on static ridesharing matching,this mechanism is designed for dynamic ridesharing scenario.In addition,in order to ensure the accuracy and efficiency of the privacy-preserving ridsharing service,based on H2H indexing technology and homomorphic encryption algorithms,an efficient privacy-preserving accurate shortest road distance query algorithm is proposed,which makes users can also enjoy high-quality ridesharing matching services with privacy protection.Finally,security analysis prove that the mechanism can effectively protect the location privacy of riders and drivers,and simulation experiments prove the practicability and efficiency of the scheme.