Biometric information security based on double chaotic rotating diffusion

Abstract

Biometric technology is increasingly being used in various areas, including government law enforcement, exit and entry management, visitor access control, user identification, and daily attendance management for companies. This technology simplifies the procedure of user identity verification and reduces the time required for verification. However, the security of biological data stored in the system can be overlooked. To address this, we propose a secure biometric feature matching framework that encrypts all information stored in the biometric system. The system decrypts and extracts feature values only when recognition and matching are required, enabling secure matching judgment. This framework protects private data in the biometric system from illegal theft, tampering, and destruction, and promotes research and practical application of biometric security technology. To fully ensure system data security, we propose an adaptive rotation diffusion image encryption algorithm based on double chaos. The algorithm uses double chaos to control image scrambling and leverages the random characteristics of chaos. The algorithm adopts six different rotation diffusion methods, and different plaintext images lead to completely different diffusion methods, making the algorithm adaptive and effective against selected plaintext attacks. Experimental simulations and performance analysis confirm the feasibility and superiority of the proposed algorithm.