Efficient and Secure Spatial Range Query over Large-scale Encrypted Data

• Main Authors: Miao, Yinbin, Xu, Chao, Zheng, Yifeng, Liu, Ximeng, Meng, Xiangdong, Deng, Robert H.
• Format: Conference Proceeding
• Language: English
• Subjects: Computer architecture; Cryptography; Distributed databases; dual-cloud; encrypted spatial data; Filtering algorithms; large-scale dataset; Privacy; privacy-preserving; Query processing; Spatial databases; Spatial range query
• ISSN: 2575-8411
• DOI: 10.1109/ICDCS57875.2023.00055

Spatial range query enjoys widespread application scenarios due to the ever-growing geo-positioning technology in recent years. Huge amounts of encrypted geo-location data are being outsourced to cloud servers to alleviate local storage and computational overheads without leaking sensitive information. However, most existing Privacy-preserving Spatial Range Query (PSRQ) cannot achieve high efficiency while satisfying strong security over large-scale encrypted spatial data. To strike a best possible balance between security and efficiency, we propose a novel efficient Privacy-preserving Spatial Range Query (eP-SRQ) scheme in dual-cloud architecture over large-scale dataset. Specifically, we propose an efficient PSRQ scheme by designing a novel index structure based on Geohash algorithm, Circular Shift and Coalesce Zero-Sum Garbled Bloom Filter (CSC-ZGBF) and Symmetric Homomorphic Encryption (SHE), which makes the computational complexity of query process independent of dataset size. Formal security analysis proves that our scheme can achieve Indistinguishability against Chosen-Plaintext Attack (IND-CPA), and extensive experiments prove that our scheme is feasible in real-world applications.