Research On Privacy Protection Mechanisms For Location-Based Services

With the proliferation of mobile devices with location-aware functions,location-based service(LBS)has become one of the most popular mobile applications.As the volume of data increases dramatically in recent years,in order to reduce storage and computing costs,location service provider(LSP)outsources a large amount of LBS data onto the cloud server.However,while cloud storage provides convenience and stability,it also leads to data security and user privacy leakage.Therefore,secure storage and calculation of LBS data in an untrusted cloud environment have become a critical issue that needs to be figured out imminently.This thesis pay attention to data security and user privacy protection in LBS outsourcing data services,and the main contributions of this thesis are as follows:1.A privacy protection scheme for LBS outsourcing data is constructed,which supports interval query,such as a query that satisfies the interest points of price,rating and sales volume within a specific interval.Firstly,a geographic range query is achieved based on the enhanced asymmetric scalar-product preserving encryption algorithm to realize.Then,the public key searchable encryption algorithm is used to match the keyword and realizes the privacy protection search.Finally,the lightweight algebraic operation between matrices can enable users to query the record interval of POI ciphertext without revealing the query interval.This scheme not only ensures the data security of LSP but also protects the privacy of users' query.Security analysis and experiments demonstrate that the scheme not only accomplishes privacy protection but also keeps efficient performance.2.A privacy protection scheme for LBS outsourcing data that supports the Top-k query is proposed.To ensure the data confidentiality of LSP and user query mode's privacy,firstly,an enhanced asymmetric scalar-product preserving encryption algorithm and public key searchable encryption algorithm is chosen to degrade the computational cost of the scheme and realize the privacy protection search.Then,an efficient and secure index structure is constructed by using coded quadtree and bloom filter.According to the encrypted query request,the cloud server can quickly locate the user's query region,thus improving retrieval efficiency.Finally,the security of the presented scheme is proved by the random oracle model,and experiments display that the put forward scheme has preferable to similar schemes.