安全的人脸模板生成通过局部区域哈希

Rohit Pandey, V. Govindaraju
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引用次数: 14

摘要

安全性是生物识别认证系统实际部署中的一个重要方面。原始形式的生物特征数据是不可替代的,因此必须加以保护。这通常是以降低匹配准确性或失去真正的无密钥生物识别身份验证所能提供的便利为代价的。在本文中,我们解决了现有的人脸模板保护方案的缺点,并展示了本地化方法的优点。我们提出了一个框架,利用面部局部区域的特征来实现精确匹配,从而实现SHA-256等哈希函数提供的安全性。我们研究了不同特征提取器的匹配精度,并提出了在合理的现实世界假设下量化该方案所提供的安全性的措施。在Multi-PIE人脸数据库上验证了该方法的有效性。
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Secure face template generation via local region hashing
Security is an important aspect in the practical deployment of biometric authentication systems. Biometric data in its original form is irreplaceable and thus, must be protected. This often comes at the cost of reduced matching accuracy or loss of the true key-less convenience biometric authentication can offer. In this paper, we address the shortcomings of current face template protection schemes and show the advantages of a localized approach. We propose a framework that utilizes features from local regions of the face to achieve exact matching, and thus, enables the security offered by hash functions like SHA-256. We study the matching accuracy of different feature extractors, and propose measures to quantify the security offered by the scheme under reasonable real-world assumptions. The efficacy of our approach is demonstrated on the Multi-PIE face database.
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