Based blockchain-PSO-AES techniques in finger vein biometrics: A novel verification secure framework for patient authentication

The main objective of this study is to propose a novel verification secure framework for patient authentication between an access point (patient enrolment device) and a node database. For this purpose, two stages are used. Firstly, we propose a new hybrid biometric pattern model based on a merge algorithm to combine radio frequency identification and finger vein (FV) biometric features to increase the randomisation and security levels in pattern structure. Secondly, we developed a combination of encryption, blockchain and steganography techniques for the hybrid pattern model. When sending the pattern from an enrolment device (access point) to the node database, this process ensures that the FV biometric verification system remains secure during authentication by meeting the information security standard requirements of confidentiality, integrity and availability. Blockchain is used to achieve data integrity and availability. Particle swarm optimisation steganography and advanced encryption standard techniques are used for confidentiality in a transmission channel. Then, we discussed how the proposed framework can be implemented on a decentralised network architecture, including access point and various databases node without a central point. The proposed framework was evaluated by 106 samples chosen from a dataset that comprises 6000 samples of FV images. Results showed that (1) high-resistance verification framework is protected against spoofing and brute-force attacks; most biometric verification systems are vulnerable to such attacks. (2) The proposed framework had an advantage over the benchmark with a percentage of 55.56% in securing biometric templates during data transmission between the enrolment device and the node database.