Double Cancelable Hashing for Protecting Biometrics of Users in Crowd

Smart gates are considered one of the most important methods for managing crowds. Often, methods of authentication and verification of users depend on the user’s biometric fingerprints, such as hand or eye prints. Sending a picture of the fingerprint or eye to the server for verification is deemed unacceptable, especially in crowds, as it will significantly impact service performance in addition to imposing a heavy load on the network. Another, more serious challenge is related to the security and privacy of this data. If a user’s fingerprint is stolen, it implies that all systems and services related to it, whether financial, medical, or otherwise, will be vulnerable to hacking. Unfortunately, the use of the traditional hash function is not sufficiently strong against a Replay Attack, and integration with blockchain requires substantial resources and suffers from delays that may impact the quality of sensitive services. In this paper, a Hash Function is proposed to enhance the level of privacy and security of biometric information. The hashing process will be doubled on one hand, and fog computing will be employed as an intermediary and additional protection on the other hand. Finally, the proposed technology will provide a solution to the problem of Relay Attack. The effectiveness and applicability of the proposed approach will be implemented and assessed.