Research On Access Control And Privacy Protection Based On Spatiotemporal Constraints

In real life,the Cloud Service Provider(CSP)allows the Data Owner(DO)to define the corresponding access constraints,and upload the data it needs to publish to the cloud server with rich functions and powerful computing capabilities.At the same time,the security of the data in the server is ensured.With the support of cloud computing technology,Location Based Service(LBS)can provide mobile users with convenient recommendation services,but it also brings the risk of information leakage.The LBS data may contain the user's private information,such as home,address,work,and entertainment venues.The leakage of LBS service information may bring higher security threats to users.The traditional Attribute Based Encryption(ABE)based solution uses static attribute-based access strategies to achieve fine-grained data security protection.The traditional ABE scheme cannot effectively deal with the access control of a continuous range of attributes,and cannot be adapted to data security scenarios where the attribute takes values within a certain dynamic range and achieves access control,such as data access control based on temporal and spatial.For this reason,this paper proposes a Temporal-Spatial Compare Attribute Based Encryption(TSC-ABE)scheme to combine Ciphertext Policy Attribute Based Encryption(CP-ABE)and Compare Attribute Based Encryption(CBE)is introduced into the algorithm encryption and decryption process,and at the same time,the structure of the access tree is redesigned to support the constraints of related spatio-temporal attributes,and to achieve access control constraints of different ranges of attributes on the integer set.The TSC-ABE solution solves the problem that traditional solutions cannot verify users in Temporal-Spatial dimensions.And the security proof and performance analysis show that the scheme avoids the privacy leakage of end users during data access with reasonable expenses.The solution outsources most decryption operations to the cloud,reducing the computing overhead on the user side.Generalization and perturbation are heuristic schemes to realize LBS privacy protection.This paper proposes a privacy protection scheme for users to continuously query LBS.The solution uses Geohash coding to construct a generalized area of candidate anonymous locations,and uses a centralized service architecture to achieve location privacy protection based on k-anonymous LBS.The solution replaces the location information requested by the user with an anonymous location set,and quantifies the false location information of the user in space through geometric constraints.The experimental results show that the proposed LBS privacy protection algorithm can achieve higher LBS query efficiency,improve the anonymous entropy of users and effectively resist Temporal-Spatial correlation attacks,and has a good privacy protection effect.