CANS 2021, 20th International Conference on Cryptology and Network Security, 13-15 December 2021, Vienna, Austria
Leveraging on function-hiding Functional Encryption (FE) and inner-product-based matching, this work presents a practical privacy-preserving face identification system with two key novelties: switching functionalities of encryption and key generation algorithms of FE to optimize matching latency while maintaining its security guarantees, and
identifying output leakage to later formalize two new attacks based on it with appropriate countermeasures. We validate our scheme in a realistic face matching scenario, attesting its applicability to pseudo real-time one-use face identification scenarios like passenger identification.
© Springer. Personal use of this material is permitted. The definitive version of this paper was published in CANS 2021, 20th International Conference on Cryptology and Network Security, 13-15 December 2021, Vienna, Austria and is available at : https://doi.org/10.1007/978-3-030-92548-2_4