IDFace: Face Template Protection for Efficient and Secure Identification
Sunpill Kim, Seunghun Paik, Chanwoo Hwang, Dongsoo Kim, Junbum Shin, Jae Hong Seo

TL;DR
IDFace introduces an efficient homomorphic encryption-based face template protection method that enables fast and secure identification in large-scale biometric databases, significantly improving privacy without sacrificing performance.
Contribution
The paper presents IDFace, a novel HE-based face identification approach with two techniques for efficient encrypted search and template encoding, achieving practical speed and security.
Findings
Identifies a face from 1 million encrypted templates in 126ms
Achieves only 2x overhead compared to plaintext identification
Provides secure face template protection with practical efficiency
Abstract
As face recognition systems (FRS) become more widely used, user privacy becomes more important. A key privacy issue in FRS is protecting the user's face template, as the characteristics of the user's face image can be recovered from the template. Although recent advances in cryptographic tools such as homomorphic encryption (HE) have provided opportunities for securing the FRS, HE cannot be used directly with FRS in an efficient plug-and-play manner. In particular, although HE is functionally complete for arbitrary programs, it is basically designed for algebraic operations on encrypted data of predetermined shape, such as a polynomial ring. Thus, a non-tailored combination of HE and the system can yield very inefficient performance, and many previous HE-based face template protection methods are hundreds of times slower than plain systems without protection. In this study, we propose…
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Taxonomy
TopicsBiometric Identification and Security
