Research On Key Technologies Of Ciphertext Queries And Retrieval For Privacy-preserving In Cloud Computing

With the advent of cloud computing,more and more data owners are motivated to outsource their data to cloud servers in consideration of convenience and cost.However,adversaries may try to gain access to sensitive data,and curious or malicious administrators may capture and leak data.In order to realize privacy preservation,sensitive data should be encrypted before outsourcing.The encrypted data will lose some characteristics of the plaintext,such as some traditional operations on the plaintext(e.g.,SQL queries,document retrieval,etc.)cannot be performed over the ciphertext.The dissertation focuses on the encrypted database queries and encrypted document retrieval for privacy-preserving in cloud computing.Combining homomorphic encryption,order-preserving encryption and searchable encryption technologies,it presents a series of encrypted database queries algorithms and encrypted document retrieval schemes,and analyzes the performance of the proposed algorithms and schemes.The contributions are summarized as follows.(1)For the needs of encrypted database query,the dissertation designs an encrypted database model that supports SQL queries,called QSDB(queryable and secure database model).It encrypts sensitive data and can execute SQL queries over encrypted data.Furthermore,experiments on the real-world data sets were conducted to demonstrate the efficiency and practicality of the proposed model.(2)To solve the issue of repeated encryptions reduce query efficiency,the dissertation presents an efficient homomorphic order-preserving encryption algorithm FHOPE(efficient homomorphic order-preserving encryption),which allows cloud server to perform complex SQL queries that contain different operators(such as addition,multiplication,order comparison,and equality checks)over encrypted data without repeated encryption.These operators are data interoperable,so they can be combined to formulate complex SQL queries.The experiment results show that,compared with the existing approaches,the FHOPE algorithm incurs less overhead on computation and communication.Hence,it is suitable for large batch complex SQL queries over encrypted data in cloud environment.(3)To solve the issue of low retrieval efficiency of the encrypted documents and inaccurate retrieval results,the dissertation proposes an efficient and accurate searchable encryption scheme FASE(efficient and accurate searchable encryption)that supports accurate top-k multi-keyword retrieval.The scheme takes advantage of a homomorphic order-preserving encryption algorithm to encrypt the index and query vectors.In addition,it implements the secure calculation of relevance score between encrypted index and query vectors,and protects the privacy of ranking operator.Compared to the traditional method,there are no dummy keywords added to the query vector and document vector,and the top-k search precision of the FASE scheme is 100%.To improve the search efficiency,a large number of irrelevant documents are effectively filtered by matching the document mark vector and query mark vector.Furthermore,according to the two round ranking of the keyword matching degree and the relevance score,not only more accurate search result is returned,but also the search efficiency is also further improved.The theoretical analysis and experimental results demonstrate that the FASE scheme can achieve fast and accurate multi-keyword ranking search.(4)To solve the issue of ignoring spelling errors and semantic expansion of keywords in most schemes,the dissertation proposes an effective fuzzy semantic searchable encryption scheme FSSE(fuzzy semantic searchable encryption)that supports multi-keyword search over encrypted data in cloud computing.The scheme exploits a keyword fingerprint generation algorithm to generate a fingerprint set of the keyword dictionary and a fingerprint of the query keywords,and employ Hamming distance to quantify keywords similarity.Based on the proposed fingerprint generation algorithm and Hamming distance,it realizes a fuzzy search scheme.Furthermore,it utilizes the semantic expansion technique to expand query keywords and calculate the semantic similarity between the query keywords and the expanded word of the query keywords to achieve the semantic search.To improve the search efficiency,it constructs an inverted index structure and use the vector intersection matching as well as short-circuit matching operations to effectively filter irrelevant documents.The theoretical analysis and experimental results demonstrate that the proposed scheme satisfies the security guarantee of searchable encryption and is more efficient in comparison with the state of the art schemes.