Biometrics combined with cryptography can be employed to solve the conceptual and factual identity frauds in digital authentication. Biometric traits are proven to provide enhanced security for detecting crimes because of its interesting features such as accuracy, stability, and uniqueness. Although diverse techniques have been raised to address this objective, limitations such as higher computational time, minimal accuracy, and maximum recognition time remain. To overcome these challenges, an enhanced iris recognition approach has been proposed based on hyperelliptic curve cryptography (HECC). The proposed study uses the 2D Gabor filter approach for perfect feature extraction in iris preprocessing. A lightweight cryptographic scheme called HECC was employed to encrypt the iris template to avoid intentional attack by the intruders. The benchmark CASIA Iris V-4 and IITD iris datasets were used in the proposed approach for experimental analysis. The result analysis witnessed that the prime objective of the research such as lesser false acceptance rate, lesser false rejection rate, maximum accuracy of 99.74%, maximum true acceptance rate of 100%, and minimal recognition time of 3 seconds has been achieved. Also, it has been identified that the proposed study outperforms other existing well-known techniques.

中文翻译：

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使用虹膜预处理和超椭圆曲线密码技术进行安全身份验证的增强型生物特征识别

结合密码术的生物识别技术可用于解决数字身份验证中的概念和事实身份欺诈。由于具有生物识别特征的准确性，稳定性和唯一性等有趣特征，因此生物特征被证明可以提高犯罪侦查的安全性。尽管已经提出了多种技术来解决此目标，但是仍然存在诸如更高的计算时间，最小的准确性和最大的识别时间之类的限制。为了克服这些挑战，已经提出了一种基于超椭圆​​曲线密码学（HECC）的增强型虹膜识别方法。提出的研究使用2D Gabor滤波器方法在虹膜预处理中完美提取特征。采用一种称为HECC的轻量级加密方案来加密虹膜模板，以避免入侵者的故意攻击。基准CASIA Iris V-4和IITD虹膜数据集用于拟议的实验分析方法。结果分析表明，该研究的主要目的是达到较小的错误接受率，较小的错误拒绝率，最大准确度为99.74％，最大真实接受率为100％和最小识别时间为3秒。此外，已经确定，拟议的研究优于其他现有的众所周知的技术。