Research On Privacy-preserving Mechanism Of Range Query Based On Location-Based Service In Cloud Environment

The development of wireless communication and mobile positioning technology promotes the application of location-based services(LBS)in mobile terminals.With the maturity of cloud computing technology,LBS providers also tend to outsource services to cloud servers to reduce their own storage and management costs.At present,applications based on LBS are ubiquitous,but as people's awareness of privacy preservation increases,the security of LBS has gradually aroused people's concerns.In addition,as a private commercial resource of LBS providers,location data also has the risk of leakage after being outsourced to cloud servers.The privacy problems of users and LBS providers in cloud environment can not be ignored.How to design a secure and effective query scheme in cloud environment has become an urgent problem.Range query is a basic query in LBS.By analyzing the query forms of range query in LBS,it is found that users' query requests usually include a variety of query attributes and arbitrary query range.Based on the above findings,this paper studies the privacy preservation of multi-keyword range query and geometric range query in cloud environment,aiming to preserve the users' query privacy and the LBS provider's data privacy while realizing efficient range query.The main work is as follows:(1)A privacy-preserving scheme supporting multi-keyword range query in cloud environment is designed.Firstly,the scheme uses Hilbert curve to divide the region into atomic regions,and uses the curve coding to identify the atomic region.The user's query range is transformed into a coding set and is encrypted.Secondly,the scheme randomizes the user's query attributes to Bloom Filter values,and establishes an attribute-hierarchical index of the location data in units of atomic regions.Using encrypted coding set and randomized Bloom Filter values to represent the user's query scope and attributes,the specific query information can be hidden.Finally,the scheme uses proxy re-encryption technology to encrypt location data,which can ensure the data privacy of LBS provider and realize the sharing of location data among users.Efficiency analysis shows that the scheme can realize the batch query of location data in sub linear time,so it is more suitable for the query of large-scale data sets in the data outsourcing scenario.(2)The privacy-preserving scheme supporting geometric range query in cloud environment is designed.Based on the division of regions by Hilbert curve,for irregular query range,the scheme constructs the vector form of query range and location data,and uses SSW predicate to encrypt and calculate the inner product of location vector and query vector in secret,so as to judge the relationship between geometric range and location data in any shape.The scheme can realize the accurate query of any range in the time of sub linear under the premise of ensuring the privacy of users and LBS providers.In addition,the case that the location data is taken from rational number domain is fully considered in the construction of location vector,so it is more suitable for the application scenario of precise LBS.