Safe online fingerprint matching method

Abstract

The invention relates to a safe online fingerprint matching method, which comprises the following steps that: in a safety authentication center initialization stage, a safety authentication center generates system parameters, a user and a service provider register in the safety authentication center to generate respective public and private key pairs, and user fingerprint characteristics are acquired and template data are submitted; in the user template data authorization stage, after the user registers at the service provider, the service provider applies to the security authentication centerto obtain template data of the user; in the user service request stage, a user side collects feature information of a user, and temporary verification fingerprint ciphertext information is generatedby using a homomorphic BGN cryptographic algorithm; and a ciphertext matching stage: after receiving the verification request of the user, the service provider matches the verification request with the template data of the user in the database, if the matching result is true, the service provider accepts the service request of the user, otherwise, the service provider refuses the service request of the user. Efficient and safe online fingerprint authentication is achieved, and the contradiction between the uncredibility of service providers and the privacy of user fingerprint features is solved.

Description

technical field [0001] The invention belongs to the field of information security and privacy protection, and specifically relates to a safe online fingerprint matching method, which uses a homomorphic BGN encryption algorithm to protect the privacy of user fingerprint features and performs feature matching in a ciphertext state. Background technique [0002] Biometric-based identification was first proposed in 1994. However, the security of the biometric identification system has only begun to receive widespread attention in recent years. The different encryption types of biometric data can be divided into: feature template encryption; searchable encryption; homomorphic encryption; matrix encryption. In 2006, Jules et al. proposed a Fuzzy Vault method, which maps the biometric data to the polynomial of the key construction to obtain the real point, then adds a large number of random hash values, and inputs the biometric data during verification. When a sufficient number of...

AI Technical Summary

Problems solved by technology

This method better solves the contradiction between the accuracy of the cryptographic system and the fuzziness of biological characteristics, but the Fuzzy Vault method has serious security flaws: (1) The data of the original feature point template can be obtained by cross-comparing multiple fuzzy vaults ; (2) Once the key is stolen, the attacker can replace part of the random hash value with other values, and can pass the system verification by verifying these values ​​to pretend to be a legitimate user

However, the above-mentioned fully homomorphic encryption technology has high computational complexity and high implementation cost, while some homomorphic encryption algorithms support fewer calculation methods and cannot be fully applied to complex biometric data matching calculations.

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