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Cryptographically Secure Biometrics

机译：加密安全的生物识别

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摘要

Biometric systems usually do not possess a cryptographic level of security: it has been deemed impossible to perform a biometric authentication in the encrypted domain because of the natural variability of biometric samples and of the cryptographic intolerance even to a single bite error. Encrypted biometric data need to be decrypted on authentication, which creates privacy and security risks. On the other hand, the known solutions called "Biometric Encryption (BE)" or "Fuzzy Extractors" can be cracked by various attacks, for example, by running offline a database of images against the stored helper data in order to obtain a false match. In this paper, we present a novel approach which combines Biometric Encryption with classical Blum-Goldwasser cryptosystem. In the "Client - Service Provider (SP)" or in the "Client -Database - SP" architecture it is possible to keep the biometric data encrypted on all the stages of the storage and authentication, so that SP never has an access to unencrypted biometric data. It is shown that this approach is suitable for two of the most popular BE schemes, Fuzzy Commitment and Quantized Index Modulation (QIM). The approach has clear practical advantages over biometric systems using "homomorphic encryption". Future work will deal with the application of the proposed solution to one-to-many biometric systems.
机译：生物识别系统通常不具备加密级别的安全性：由于生物识别样本的自然变异性以及甚至对于单次咬人错误的加密不容忍性，人们也认为无法在加密域中执行生物识别认证。加密的生物特征数据需要在身份验证时进行解密，这会带来隐私和安全风险。另一方面，已知的称为“生物特征加密（BE）”或“模糊提取器”的解决方案可能会受到各种攻击的破坏，例如，通过针对存储的辅助数据脱机运行图像数据库以获得错误匹配。在本文中，我们提出了一种将生物特征加密与经典Blum-Goldwasser密码系统相结合的新颖方法。在“客户端-服务提供商（SP）”或“客户端-数据库-SP”体系结构中，可以在存储和身份验证的所有阶段对生物特征数据进行加密，从而使SP永远无法访问未加密的数据生物特征数据。结果表明，该方法适用于两种最流行的BE方案：模糊承诺和量化索引调制（QIM）。与使用“同态加密”的生物识别系统相比，该方法具有明显的实际优势。未来的工作将涉及将建议的解决方案应用于一对多生物识别系统的问题。

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