Compression-Based Cancelable Multi-Biometric System

Autor: Emad A. Elshazly, Fatma G. Hashad, Ahmed Sedik, Fathi E. Abd El-Samie, Nariman Abdel-Salam
Rok vydání: 2022
DOI: 10.21203/rs.3.rs-2241969/v1
Popis: The issue of cybersecurity is one of the important fields which is involved in different research trends. Biometric security is one of these trends which is involved in several applications such as access control systems and online identity verification. The protection of human biometrics can be performed using both bi-directional and unidirectional encryption. The unidirectional encryption is carried out based on cancelable biometric techniques. This paper proposes a cancelable biometric system based on image composition, deep dream, and hashing techniques. The objective of the proposed system is to generate visual and text cancelable biometrics. The visual cancelable templates are generated using image composition and deep dream, while the text templates are generated using SHA hashing techniques. The proposed system is validated by multi-biometric inputs including iris, palm, face, and fingerprint biometrics. In addition, it is evaluated in both visual and text forms. The simulation results reveal that the proposed system appears a superior performance among the works which handle this problem.
Databáze: OpenAIRE