SEEK: Secure and Efficient Encrypted Keyword Search For Privacy-Preserving Messaging Protocols
Researchers propose SEEK, a homomorphic-encryption plus 2PC protocol for encrypted keyword search that hides keywords while detecting matches.
SEEK partitions messages into ciphertext fragments with minimum sufficient overlap and homomorphically correlates them using encrypted keyword trapdoors, combined with 2PC-based selected decoding, blinded zero testing, and secure aggregation. It reduces sender-side encryption and upload overhead by up to two orders of magnitude over state-of-the-art baselines and computes correlations up to 5.47x faster, revealing only the keyword presence bit while hiding contents, counts, and locations. A prototype achieves 1.92 seconds online computation per search on a weekly messaging history and is realized as a web and cross-platform mobile application.
- Combines homomorphic encryption with two-party computation for keyword search
- Cuts sender-side encryption and upload overhead by up to two orders of magnitude
- Reveals only match presence, hiding keyword, contents, counts, and locations
- Achieves 100% accuracy under case variations with 1.92 s per search
Full article205 words · extracted from arxiv.org · click to collapse
Encrypted communication protects sensitive user data but can facilitate harmful or unlawful exchanges, creating a trade-off between detecting dangerous messages and preserving end-user privacy. To address this, we propose SEEK, a practical and efficient encrypted keyword-search protocol for privacy-preserving messaging that combines homomorphic encryption with secure two-party computation (2PC). SEEK first partitions messages into ciphertext fragments with the minimum sufficient overlap, then homomorphically correlates them using encrypted keyword trapdoors. For long messages, this design can reduce sender-side encryption and upload overhead by up to two orders of magnitude over state-of-the-art baselines. It supports ASCII case-insensitive matching with one fixed-size encrypted trapdoor and one homomorphic multiplication per fragment, yielding up to 5.47x faster correlation computation than the strongest fragmentation-based baselines. SEEK then invokes 2PC-based selected decoding, blinded zero testing, and secure aggregation, revealing only the keyword presence-or-absence bit while hiding the keyword, its length, message contents, match counts, and locations. SEEK achieves 100% accuracy under case variations that result in exact-matching failures, without requiring additional trapdoors or online communication. We further realize SEEK as an end-to-end web and cross-platform mobile application. Prototype evaluation on a weekly messaging history yields an online computation time of 1.92 s per search, demonstrating the practical feasibility and efficiency of SEEK.
Text extracted automatically; images, tables and formatting may be missing. Original: https://arxiv.org/abs/2609.18459