General Framework to Evaluate Unlinkability in Biometric Template Protection Systems (2311.04633v1)

Abstract: The wide deployment of biometric recognition systems in the last two decades has raised privacy concerns regarding the storage and use of biometric data. As a consequence, the ISO/IEC 24745 international standard on biometric information protection has established two main requirements for protecting biometric templates: irreversibility and unlinkability. Numerous efforts have been directed to the development and analysis of irreversible templates. However, there is still no systematic quantitative manner to analyse the unlinkability of such templates. In this paper we address this shortcoming by proposing a new general framework for the evaluation of biometric templates' unlinkability. To illustrate the potential of the approach, it is applied to assess the unlinkability of four state-of-the-art techniques for biometric template protection: biometric salting, Bloom filters, Homomorphic Encryption and block re-mapping. For the last technique, the proposed framework is compared with other existing metrics to show its advantages.

• The paper proposes a systematic framework with local and global metrics to quantify unlinkability in biometric template protection systems.
• It validates the framework by applying it to four different protection methods, examining how scores impact data linking across applications.
• The research provides numerical evidence that the framework effectively identifies unlinkability levels and areas where privacy may be compromised, aiding standardized privacy evaluations.

A General Framework for Evaluating Unlinkability in Biometric Template Protection Systems

The paper "General Framework to Evaluate Unlinkability in Biometric Template Protection Systems" addresses a significant challenge in biometric security: ensuring the unlinkability of biometric templates. With the increasing deployment of biometric recognition systems, the protection of biometric data has become crucial due to the privacy concerns related to cross-matching and identity theft. This research provides a systematic framework for quantifying unlinkability, a critical aspect that lacks standardization, compared to irreversibility, in the international standard ISO/IEC 24745.

Overview of Proposed Framework

The authors introduce a novel methodology, building upon existing concepts drawn from forensic analysis and likelihood-ratio theory. They propose two distinct metrics: a local measure, $\mathrm{D}_{\leftrightarrow} (s)$, which assesses unlinkability at different score thresholds, and a global measure, $\mathrm{D}_{\leftrightarrow}^{\mathit{sys}}$, that evaluates the overall unlinkability of a biometric system.

To validate this framework, they examine its application on four diverse biometric template protection methods: biometric salting, Bloom filters, homomorphic encryption, and block re-mapping. Each of these methods is evaluated for unlinkability using standardized score distributions derived from mated and non-mated samples. The research highlights how varying scores impact the ability to link biometric data across different applications or databases.

Numerical Findings and Claims

The paper provides strong numerical evidence supporting the framework's efficacy across different protection schemes. For instance, systems utilizing biometric salting and Bloom filters demonstrated high unlinkability in the evaluation, indicating substantial overlap in mated and non-mated score distributions. The framework successfully identifies regions in the score domain where unlinkability is compromised, offering a more detailed understanding than binary approaches.

Implications and Future Directions

This research not only advances biometric privacy by addressing the under-explored area of unlinkability but also sets the stage for a broader adoption of privacy-preserving biometric systems. The ability to quantify unlinkability systematically is crucial for standardizing comparisons across different systems, paving the way for competitive evaluations in compliance with privacy regulations, such as the GDPR.

Future research could extend this framework in several directions. The integration of additional biometric characteristics and protection schemes could enrich the generalizability of the results. Moreover, exploring the interplay between unlinkability, template renewability, and system accuracy could offer deeper insights into optimizing biometric security solutions.

Conclusion

By laying down a quantitative framework for unlinkability, this paper contributes to a substantial gap in biometric template security. It emphasizes the need for objective benchmarks and encourages further development in privacy-preserving technologies. The proposed metrics provide a foundation for evaluating current and future biometric systems, ensuring a balance between usability and privacy protection. These advances are vital for the ethical and secure deployment of biometrics in a privacy-aware society.