网络与信息安全学报 (Oct 2023)
Novel fingerprint key generation method based on the trimmed mean of feature distance
Abstract
In recent years, biometrics has become widely adopted in access control systems, effectively resolving the challenges associated with password management in identity authentication.However, traditional biometric-based authentication methods often lead to the loss or leakage of users’ biometric data, compromising the reliability of biometric authentication.In the literature, two primary technical approaches have been proposed to address these issues.The first approach involves processing the extracted biometric data in a way that the authentication information used in the final stage or stored in the database does not contain the original biometric data.The second approach entails writing the biometric data onto a smart card and utilizing the smart card to generate the private key for public key cryptography.To address the challenge of constructing the private key of a public key cryptosystem based on fingerprint data without relying on a smart card, a detailed study was conducted on the stable feature points and stable feature distances of fingerprints.This study involved the extraction and analysis of fingerprint minutiae.Calculation methods were presented for sets of stable feature points, sets of equidistant stable feature points, sets of key feature points, and sets of truncated means.Based on the feature distance truncated mean, an original fingerprint key generation algorithm and key update strategy were proposed.This scheme enables the reconstruction of the fingerprint key through re-collecting fingerprints, without the need for direct storage of the key.The revocation and update of the fingerprint key were achieved through a salted hash function, which solved the problem of converting ambiguous fingerprint data into precise key data.Experiments prove that the probability of successfully reconstructing the fingerprint key by re-collecting fingerprints ten times is 0.7354, and the probability of reconstructing the fingerprint key by re-collecting fingerprints sixty times is 98.06%.
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