Biometric Template Protection: Bridging the performance gap between theory and practice

Abstract

Abstract-Biometric recognition is an integral component of modern identity management and access control systems. Due to the strong and permanent link between individuals and their biometric traits, exposure of enrolled users' biometric information to adversaries can seriously compromise biometric system security and user privacy. Numerous techniques have been proposed for biometric template protection over the last 20 years. While these techniques are theoretically sound, they seldom guarantee the desired non-invertibility, revocability, and non-linkability properties without significantly degrading the recognition performance. The objective of this work is to analyze the factors contributing to this performance gap and highlight promising research directions to bridge this gap. Design of invariant biometric representations remains a fundamental problem, despite recent attempts to address this issue through feature adaptation schemes. The difficulty in estimating the statistical distribution of biometric features not only hinders the development of better template protection algorithms, but also diminishes the ability to quantify the non-invertibility and non-linkability of existing algorithms. Finally, achieving nonlinkability without the use of external secrets (e.g., passwords) continues to be a challenging proposition. Further research on the above issues is required to cross the chasm between theory and practice in biometric template protection.

Unlinkable improved multi-biometric iris fuzzy vault

“…Consequentially, compared to conventional recognition systems, biometric cryptosystems suffer from a significant decrease in biometric performance. Multi-biometric cryptosystems, which should be designed to combine multiple biometric characteristics at feature level [21], might bridge the gap between biometric performance and privacy protection [19].…”

“…Apart from fulfilling the above properties, an ideal biometric cryptosystem shall not cause a decrease in biometric performance with respect to the corresponding unprotected system [19]. The vast majority of existing techniques do not satisfy desired template protection requirements in practice, mostly resulting in a trade-off between privacy protection and biometric performance [20].…”

Unitary Transform-Based Template Protection and Its Application to <i>l</i>²-norm Minimization Problems

“…In addition, the entropy of the parameter p i is generally reduced by applying p i to a templates set, D or D i globally. Many researchers have been seeking a trade-off between irreversibility and recognition performance as described in [30]- [32], because high recognition performance can be achieved only when the protected biometric reference retains all the discriminatory information contained in the original template. This study shows a new result, namely templates protected by a unitary transform can provide the same recognition performance in l 2 -norm minimization as that of original templates, although the templates do not satisfy "perfect security".…”

Privacy-Preserving Biometric Authentication: Challenges and Directions

“…For biometric authentication, however, a successful attack can have severe implications in the users' lives and privacy. Unlike passwords or tokens, biometric credentials cannot be kept secret or hidden, and stolen biometrics cannot be revoked as easily [1,2]. Thus, the risk of them being compromised (i.e., captured, cloned, or forged) is high and may lead to identity theft or individual profiling and tracking in case the templates are used and cross-matched in different biometric databases.…”