Department of Electrical and Computer Engineering, Inha University, Incheon 22212, Korea.
Sensors (Basel). 2021 Apr 19;21(8):2859. doi: 10.3390/s21082859.
With the recent advances in mobile technologies, biometric verification is being adopted in many smart devices as a means for authenticating their owners. As biometric data leakage may cause stringent privacy issues, many proposals have been offered to guarantee the security of stored biometric data, i.e., biometric template. One of the most promising solutions is the use of a remote server that stores the template in an encrypted form and performs a biometric comparison on the ciphertext domain, using recently proposed functional encryption (FE) techniques. However, the drawback of this approach is that considerable computation is required for the inner-pairing product operation used for the decryption procedure of the underlying FE, which is performed in the authentication phase. In this paper, we propose an enhanced method to accelerate the inner-pairing product computation and apply it to expedite the decryption operation of FE and for faster remote biometric verification. The following two important observations are the basis for our improvement-one of the two arguments for the decryption operation does not frequently change over authentication sessions, and we only need to evaluate the product of multiple pairings, rather than individual pairings. From the results of our experiments, the proposed method reduces the time required to compute an inner-pairing product by 30.7%, compared to the previous best method. With this improvement, the time required for biometric verification is expected to decrease by up to 10.0%, compared to a naive method.
随着移动技术的最新进展,生物识别验证被许多智能设备采用,作为验证其所有者身份的一种手段。由于生物识别数据泄露可能会引起严格的隐私问题,因此已经提出了许多建议来保证存储的生物识别数据(即生物识别模板)的安全性。其中最有前途的解决方案之一是使用远程服务器,以加密形式存储模板,并在密文域上执行生物识别比较,使用最近提出的功能加密(FE)技术。然而,这种方法的缺点是,底层 FE 的解密过程中使用的内配对乘积操作需要相当大的计算量,该操作在认证阶段执行。在本文中,我们提出了一种增强方法来加速内配对乘积计算,并将其应用于加速 FE 的解密操作和更快的远程生物识别验证。我们的改进有两个重要的观察结果:一是解密操作的两个参数之一在认证会话中不会频繁更改,二是我们只需要评估多个配对的乘积,而不是单个配对的乘积。从我们的实验结果来看,与之前最好的方法相比,所提出的方法将计算内配对乘积所需的时间减少了 30.7%。通过这种改进,与简单方法相比,生物识别验证所需的时间有望减少 10.0%。