BRASP: Boolean Range Queries over Encrypted Spatial Data with Access and Search Pattern Privacy
Jing Zhang, Ganxuan Yang, Yifei Yang, Siqi Wen, Zhengyang Qiu
TLDR
BRASP enables private Boolean range queries over encrypted spatial data, hiding search and access patterns from cloud servers.
Key contributions
- Introduces BRASP, a searchable encryption scheme for Boolean range queries over encrypted spatial data.
- Hides search and access patterns using index shuffling and ID-field redistribution in a dual-server setting.
- Combines Hilbert-curve encoding with encrypted inverted indexes for efficient spatial filtering and keyword matching.
- Supports dynamic updates and achieves forward security, with formal security analysis and experimental validation.
Why it matters
Existing searchable encryption often leaks sensitive search and access patterns, especially for complex spatial data, compromising user privacy. BRASP offers a novel solution, enabling secure and private Boolean range queries over encrypted spatial data. This significantly enhances data confidentiality in cloud environments.
Original Abstract
Searchable Encryption (SE) enables users to query outsourced encrypted data while preserving data confidentiality. However, most efficient schemes still leak the search pattern and access pattern, which may allow an honest-but-curious cloud server to infer query contents, user interests, or returned records from repeated searches and observed results. Existing pattern-hiding solutions mainly target keyword queries and do not naturally support Boolean range queries over encrypted spatial data. This paper presents BRASP, a searchable encryption scheme for Boolean range queries over encrypted spatial data. BRASP combines Hilbert-curve-based prefix encoding with encrypted prefix--ID and keyword--ID inverted indexes to support efficient spatial range filtering and conjunctive keyword matching. To hide the search pattern and access pattern under a dual-server setting, BRASP integrates index shuffling for encrypted keyword and prefix entries with ID-field redistribution across two non-colluding cloud servers. BRASP also supports dynamic updates and achieves forward security. We formalize the security of BRASP through confidentiality, shuffle indistinguishability, query unforgeability, and forward-security analyses, and we evaluate its performance experimentally on a real-world dataset. The results show that BRASP effectively protects query privacy while incurring relatively low computation and communication overhead. To facilitate reproducibility and further research, the source code of BRASP is publicly available at https://github.com/Egbert-Lannister/BRASP
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