Monchi: Multi-scheme Optimization For Collaborative Homomorphic Identification - Equipe Secure and Safe Hardware Access content directly
Conference Papers Year : 2024

Monchi: Multi-scheme Optimization For Collaborative Homomorphic Identification


This paper introduces a novel protocol for privacy-preserving biometric identification, named Monchi, that combines the use of homomorphic encryption for the computation of the identification score with function secret sharing to obliviously compare this score with a given threshold and finally output the binary result. Given the cost of homomorphic encryption, BFV in this solution, we study and evaluate the integration of two packing solutions that enable the regrouping of multiple templates in one ciphertext to improve efficiency meaningfully. We propose an end-to-end protocol, prove it secure and implement it. Our experimental results attest to Monchi’s applicability to the real-life use case of an airplane boarding scenario with 1000 passengers, taking less than one second to authorize/deny access to the plane to each passenger via biometric identification while maintaining the privacy of all passengers.
Fichier principal
Vignette du fichier
2024-654.pdf (837.94 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-04562874 , version 1 (06-05-2024)



Alberto Ibarrondo Luis, Ismet Kerenciler, Hervé Chabanne, Vincent Despiegel, Melek Önen. Monchi: Multi-scheme Optimization For Collaborative Homomorphic Identification. IH&MMSec 2024, 12th ACM Workshop on Information Hiding and Multimedia Security, ACM, Jun 2024, Baiona, Spain. ⟨10.1145/3658664.3659633⟩. ⟨hal-04562874⟩
168 View
17 Download



Gmail Mastodon Facebook X LinkedIn More