Generating stable biometric keys for flexible cloud computing authentication using finger vein

Abstract Cloud computing is profoundly changing the way of data storage, transfer and process. User authentication is the first security barrier for cloud computing. However, the security of traditional biometric-template-based authentication technology has been challenged because of the information leakage of biometric templates and insufficient user-key strength, which is limited by the ability of the user to memorize keys. In this paper, we propose a new bio-key generation algorithm named FVHS, which combines the advantages of both biometrics authentication and user-key authentication. It directly generates stable and sufficiently strong bio-key sequences from finger vein biometrics. Based on FVHS, a new framework for cloud computing authentication is presented that provides a more flexible, convenient, and secure user authentication. The key idea of FVHS is that through combining machine learning, biometrics, and cryptography technologies, we can mine a special feature vector from the biometrics space that can be separated and stabilized into a fixed number sequence in a higher-dimensional space. Both a theoretical analysis and experimental verification show that FVHS can extract stable bio-keys from high quality finger vein images. FVHS can extract a finger vein bio-key with a Genuine Accept Rate of more than 99.9%, while the False Accept Rate is less than 0.8% and Equal Error Rate is less than 0.5%. Meanwhile, the security strength can reach 256 bits.