Cancelable Biometric Template Protection Based on Multi-Instance Fusion: A Contralateral Iris Approach

• URL: http://arxiv.org/abs/2607.02860v1
• Date: Fri, 03 Jul 2026 01:46:11 GMT
• Title: Cancelable Biometric Template Protection Based on Multi-Instance Fusion: A Contralateral Iris Approach
• Abstract summary: This paper proposes a cancelable contralateral iris template protection scheme.<n>It satisfies the three requirements of ISO/IEC 24745: irreversibility, unlinkability, and confidentiality.<n>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.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• 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.

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