Multi-dimensional Data Order Preserving Encryption In Cloud Computing Environment

With the great advantages brought by data outsourcing now more and more IT industries are uploading their data to cloud servers.However,outsourcing data to cloud servers is often accompanied by data privacy and security risks.Nowadays,the typical solution is to encrypt your own data and upload it to the cloud server,which ensures data security but greatly decreases the efficiency of user data queries,such as our common SQL queries.The order preserving encryption scheme solves this problem by keeping the ciphertext data in the same order as the plaintext data.The existing order preserving encryption schemes focus on one-dimensional data,but the problem of order preserving encryption of multi-dimensional data is still not well solved.In this thesis,we research on the problem of order preserving encryption of multi-dimensional data in cloud computing environment,solve the problem of privacy data protection through order preserving encryption and propose two efficient multi-dimensional data order preserving encryption schemes with feature to meet practical application scenarios.The main work of this thesis is broadly divided into the following aspects:1.We provide an overview and summary of order preserving encryption schemes in cloud computing environment and schemes for multi-dimensional data range query,and we analyze the existing order preserving encryption schemes related to them and point out the corresponding advantages and disadvantages.The research background and status of research in the direction of order preserving encryption and the significance of research on multi-dimensional data order preserving encryption in the cloud computing environment are stated.2.To deal with the inefficiency of range querying of multi-dimensional ciphertext data,we proposed an order preserving encryption scheme for multi-dimensional data to support range querying of encrypted multi-dimensional data.Firstly,Bloom filter and prefix encoding techniques are used to construct indexes for each dimension of data,secondly,the property of the network data structure is used to make each dimension pre-sorted during the query process,and finally,index security is ensured by extracting the seed of the pseudo-random hash function used in Bloom filter as the secret key,and AES encryption is used for plaintext security.The scheme construction not only improves query efficiency while supporting users for fine-grained queries on data,and provides features that are more suitable for practical application scenarios.3.To deal with the problem that the security and efficiency of multi-dimensional ciphertext data Skyline query cannot be reconciled,we propose an order preserving encryption scheme for multi-dimensional data based on Skyline query.Firstly,we transform the comparison operation in Skyline query to the problem of intersection of sets and sets by calculating the dominance relationship in Skyline query,then we use Bloom filter to judge the intersection of data to complete the function of order preserving encryption.The scheme is also used to improve the security of the Skyline query by ensuring that the cloud server can compute the dominance relationship between data in the ciphertext state and finally demonstrating the feasibility of the scheme through various experiments.