Cancelable Biometric Template Protection Based on Multi-Instance Fusion: A Contralateral Iris Approach
2026-07-03 • Computer Vision and Pattern Recognition
Computer Vision and Pattern RecognitionCryptography and Security
AI summaryⓘ
The authors propose a new way to protect iris biometric data without needing extra keys or tokens, which can be easy to lose or steal. They combine iris data from both eyes and use a special method to mix and lock this data, making it very hard for hackers to retrieve original iris information. Their approach also improves recognition accuracy by using patterns from both eyes and meets international security standards. Tests on several iris datasets show their method works well compared to other protection techniques.
Biometric templatesIris recognitionCancelable biometricsIrreversibilityUnlinkabilityConfidentialityContralateral fusionMajority Vote FusionBitwise XORISO/IEC 24745
Authors
Jittarin Chaivong, Nicha Vikromrotjananan, Teekatat Piriyapittaya, Waree Kongprawechnon, Suradej Duangpummet
Abstract
Biometric templates are vulnerable to theft if stored without protection. Unlike passwords, a compromised iris cannot be reissued. Although existing cancelable biometric schemes address this problem, most still require an external key or token, introducing an additional attack surface. This paper proposes a cancelable contralateral iris template protection scheme that eliminates the need for a separate token or stored secret, satisfying the three requirements of ISO/IEC 24745: irreversibility, unlinkability, and confidentiality. The method fuses three enrollment samples per eye using Majority Vote Fusion to produce a stable template, and applies a salt-based bit permutation derived from the subject's enrollment ID. Combining the left- and right-permuted templates via a bitwise XOR produces a single Protected Fused Template. Since left and right iris patterns are statistically independent, fusing contralateral irises improves the accuracy of the system. An attacker must possess both iris codes and both salts to recover any useful information, yielding a larger effective key space than single-iris schemes. Experiments on three datasets, CASIA-IrisV4-Interval, CASIA-IrisV2 (two devices), and CASIA-Iris-Thousand, yield EERs of $0.36$\%, $4.88$\%, $10.80$\%, and $3.35$\%, respectively; the highest value reflects the more challenging cross-device scenario. These results demonstrate that our contralateral approach outperforms unprotected baselines while remaining competitive with state-of-the-art cancelable methods. %In addition, an ablation study confirms the benefit on both recognition performance and security. To the best of our knowledge, this is the first scheme to combine tokenless multi-instance fusion and contralateral binding under ISO/IEC 24745.