Privacy-Preserving Iris Recognition: Performance Challenges and Outlook
Iris-based biometric identification is increasingly recognized for its significant accuracy and long-term stability compared to other biometric modalities such as fingerprints or facial features. However, all biometric modalities are highly sensitive data that raise serious privacy and security concerns, particularly in decentralized and untrusted environments. While Fully Homomorphic Encryption (FHE) has emerged as a promising solution for protecting sensitive data during computation, existing privacy-preserving iris recognition systems face significant performance limitations that hinder their practical deployment. This paper investigates the performance challenges of the current landsc...
| Authors | Christina Karakosta, Lian Alhedaithy, William J. Knottenbelt |
|---|---|
| Primary category | cs.CR |
| Published | 27 March 2026 |
| Last updated at source | 27 March 2026 |
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