BRASP: Boolean Range Queries over Encrypted Spatial Data with Access and Search Pattern Privacy

TL;DR

BRASP is a privacy-preserving searchable encryption scheme enabling efficient Boolean range queries over encrypted spatial data, protecting search and access patterns against a dual-server setting.

Contribution

It introduces a novel scheme combining Hilbert-curve encoding and index shuffling to support secure, dynamic, and efficient spatial range queries with pattern hiding.

Findings

BRASP effectively protects query privacy with low overhead.

It supports dynamic updates and forward security.

Experimental results on real data demonstrate its practicality.

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