Secure and Efficient Online Fingerprint Authentication Scheme Based On Cloud Computing

Privacy protection of biometrics-based on cloud computing is attracting increasing attention. In 2018, Zhu et al. proposed an efficient and privacy-preserving online fingerprint authentication scheme for data outsourcing e-Finga. Under the premise of ensuring user's fingerprint data privacy and message security authentication, the e-Finga scheme can provide accurate and efficient fingerprint identity authentication services. However, our analysis shows that the temporary fingerprint in this scheme uses the deterministic encryption algorithm, which has the risk of leaking the user's fingerprint characteristics. Therefore, we propose a temporary fingerprint attack method for the e-Finga scheme. Experiments demonstrate that an adversary can analyze specific secret parameters and fingerprint features when eavesdropping on a user's temporary fingerprint ciphertext. To counter the temporary fingerprint attack, we propose a secure e-fingerprint scheme- Secure e-finger that uses the learning with errors samples, which has the homomorphic addition property, to encrypt user's temporary fingerprints. Experiments show that the secure e-finger scheme can resist the temporary fingerprint attack. Compared with the unprotected e-Finga scheme, the client running time is increased by about 6% percent, the communication cost on the user side only increased by 0.3125% percent. As a result, our solution can realize secure online fingerprint authentication without losing efficiency. Single user authentication is likely to cause the problem of excessive authority. Based on the Secure e-finger scheme, we propose a threshold scheme based on biological characteristics.