Efficient and privacy-preserving encode-based range query over encrypted cloud data

• Main Authors: LIANG, Yanrong, MA, Jianfeng, MIAO, Yinbin, SU, Yuan, DENG, Robert H.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Encryption; Cryptography; Vectors; Indexes; Codes; Servers; Costs; Searchable symmetric encryption; privacy-preserving range query; range encoder; symmetric-key hidden vector encryption; Information Security
• Online Access: https://ink.library.smu.edu.sg/sis_research/9436
• Institution: Singapore Management University

Privacy-preserving range query, which allows the server to implement secure and efficient range query on encrypted data, has been widely studied in recent years. Existing privacy-preserving range query schemes can realize effective range query, but usually suffer from the low efficiency and security. In order to solve the above issues, we propose an Efficient and Privacy-preserving encode-based Range Query over encrypted cloud data (namely basic EPRQ), which encodes the data and range by using Range Encode (REncoder), and then encrypts the codes via Additional Symmetric-Key Hidden Vector Encryption (ASHVE) technology. The basic EPRQ can achieve effective range query while ensuring privacy protection. Then, we split the codes to reduce the storage cost. We further propose an improved scheme, EPRQ+, which constructs a binary tree-based index to achieve faster-than-linear retrieval. Finally, our formal security analysis proves that our schemes are secure against Indistinguishability under Chosen-Plaintext Attack (IND-CPA), and extensive experiments demonstrate that our schemes are feasible in practice, where EPRQ+ scheme improves the storage efficiency by about 4 times and the query efficiency by about 8 times compared to the basic EPRQ.