Work

PLRQ: Practical and Less Leakage Range Query Over Encrypted Mobile Cloud Data

Year: 2024

Type: article

Abstract: As a fundamental service in mobile cloud computing, range query has attracted extensive attention. But the existing secure range query schemes not only leak data privacy but also have low query efficiency. To address those issues, we first design a novel range-matched code to convert the range query into code set matching, which aims to hide the order relationship of outsourced data as well as the index of most significant different bit. Based on the designed range-matched code, we propose aPractical andLess LeakageRangeQuery scheme over encrypted mobile cloud data (PLRQ) by integrating XOR filter and multiset hash function. Security analysis shows that PLRQ achieves semantic security and avoids data privacy leakage. Extensive experiments using real datasets demonstrate that, compared with two state-of-the-art solutions-RngMatch and LSRQ, our proposed PLRQ improves the query efficiency both by 2 orders of magnitude, and reduces the storage cost on Cloud Service Provider by about 79.5% and 73.6% respectively.

Source: IEEE Transactions on Mobile Computing

DOI: 10.1109/tmc.2024.3521366

Authors: Yunwei Wang, Xinghua Li, Yinbin Miao, Qiuyun Tong, Ximeng Liu, Robert H. Deng

Institutions: Xidian University, Hefei University of Technology, Fuzhou University, Singapore Management University

Language: English

Topic: Cryptography and Data Security

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: National Natural Science Foundation of China, Aeronautical Science Foundation of China, Fundamental Research Funds for the Central Universities

Awards: G2352548512, G2786631335, G297574523, G4365675440, G5348138716