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Iris Cancellable Template Generation Based on Indexing-First-One Hashing

机译:基于索引第一哈希的虹膜可取消模板生成

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Iris recognition system has demonstrated its strong capability in performing personal verification and identification with promising recognition accuracy. However, the conventional iris recognition system stores the unprotected iris templates in a database, which is potentially being compromised. Even though biometric template protection provides a feasible solution to secure biometric template, a trade-off between security and recognition accuracy is incurred. That is, the higher security level always trades with poor recognition accuracy and vice versa. In this paper, a new iris template protection scheme is proposed, namely "Indexing-First-One" (IFO) hashing. IFO hashing transforms the binary feature into index value with Jacaard distance preservation. The resultant template offers a good indication of inheriting similarity from the IrisCode and strong concealment of IrisCode against inversion attack as well as other major security and privacy attacks. Experiments on CASIA-v3 data set substantiate that the proposed scheme can achieve as low as 0.54 % equal error rate and well preservation of recognition performance before and after IFO hashing.
机译:虹膜识别系统已经证明了其以有希望的识别精度执行个人验证和识别的强大能力。但是,传统的虹膜识别系统将未受保护的虹膜模板存储在数据库中,这可能会受到损害。即使生物特征模板保护提供了一种可行的解决方案来保护生物特征模板,但仍需要在安全性和识别准确性之间进行权衡。也就是说,较高的安全级别始终以较差的识别精度进行交易,反之亦然。本文提出了一种新的虹膜模板保护方案,即“索引先到一”(IFO)哈希。 IFO哈希通过保留Jacaard距离将二进制特征转换为索引值。生成的模板很好地表明了可以从IrisCode继承相似性,并强力掩盖了IrisCode的反演攻击以及其他主要的安全和隐私攻击。在CASIA-v3数据集上进行的实验证明,该方案可以实现低至0.54%的均等错误率,并且在IFO哈希处理之前和之后都能很好地保持识别性能。

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