Fingerprint biometric key generation method based on deep neural network coding

Abstract

The invention discloses a fingerprint biological key generation method based on deep neural network coding. According to the method, a classic fingerprint image processing method and a deep neural network method are combined, a series of operations of blind alignment, stable feature extraction, feature sequence stabilization and the like of the fingerprint image are realized, stable feature components of different samples of the same fingerprint are extracted more accurately, and through layer-by-layer processing of the deep neural network, the method further stabilizes the fingerprint feature to the feature value, and finally realizes the high-intensity key sequence generation of the normal fingerprint image through a fingerprint key fuzzy extractor, and the length of the generated fingerprint biological key can be greater than 512 bits. According to the method, biological feature template information needing to be recorded does not exist, the risk of privacy disclosure is greatly reduced, meanwhile, a user can generate a high-safety secret key without high-intensity memory, the secret key can be used for existing public and private keys, symmetric encryption and other operations, and the safety and flexibility of fingerprint biological feature use are improved.

Description

technical field [0001] The invention belongs to the technical field of cyberspace security, and relates to a fingerprint biological key generation method based on deep neural network coding, in particular to a method for directly extracting high-intensity stable biological keys from human fingerprints through blind alignment, deep neural network recoding and other processing. The secret key method can provide a new authentication method for the existing identity authentication technology based on human fingerprints, and seamlessly integrate with the existing public-private key and symmetric encryption methods to support more convenient and safe authentication in the network. Authentication and encryption based on user fingerprints. Background technique [0002] Fingerprint identification technology is a relatively mature biometric identification technology nowadays. During its use, it needs to store the user's fingerprint feature template for authentication comparison. The f...

AI Technical Summary

Problems solved by technology

This method still retains fingerprint features and key information such as fingerprint feature distance, generation interval, and final generated biological key during the fingerprint key generation process. These information need to be kept in the local security domain, and the security of the whole method depends on the local The security of the security domain is vulnerable to attack

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