Seek speeds up secure encrypted keyword search in messaging apps
SEEK: Secure and Efficient Encrypted Keyword Search For Privacy-Preserving Messaging Protocols
Cryptography and SecurityInformation Retrieval
Summary
Encrypted messaging keeps your chats private but makes it hard to spot harmful content. The authors designed SEEK, a method that lets services securely search messages for keywords without revealing sensitive details. SEEK breaks messages into pieces and uses advanced math tricks so only a yes-or-no answer about keyword presence is revealed. It works quickly, even on long messages, and ignores differences like uppercase or lowercase letters. The authors built a prototype app to show SEEK can be practical for real use.
What this means in practice
- •For messaging app developers: Integrate secure keyword detection that preserves user privacy and reduces server load in encrypted chat platforms.
- •For cloud security teams: Enable privacy-respecting content monitoring in encrypted cloud messaging services without exposing message details.
Authors
Soumyadyuti Ghosh, Michail Maniatakos
Abstract
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.