This article presents a tutorial overview of the application of techniques of secure two-party computation (also known as secure function evaluation) to biometric identification. These techniques enable to compute biometric identification algorithms while maintaining the privacy of the biometric data. This overview considers the main tools of secure two-party computations such as homomorphic encryption, garbled circuits (GCs), and oblivious transfers (OTs) and intends to give clues on the best practices to secure a biometric identification protocol. It also presents recent trends in privacy-preserving biometric identification that aim at making it usable in real-life applications.
['Julien Bringer', 'Hervé Chabanne', 'Alain Patey']
Privacy-Preserving Biometric Identification Using Secure Multiparty Computation: An Overview and Recent Trends