Dual Chaotic Diffusion Framework for Multimodal Biometric Security Using Qi Hyperchaotic System

The proliferation of biometric authentication systems across critical domains such as financial services, healthcare, security, law enforcement, and border control necessitate robust protection mechanisms for sensitive biometric data. This paper introduces a novel dual-layer cryptographic framework leveraging four-dimensional Qi hyperchaotic dynamics for securing face and iris biometric templates. The proposed system's cryptographic foundation demonstrates exceptional randomness properties, validated through comprehensive NIST Statistical Test Suite analysis, achieving statistical significance across all 15 NIST tests suite with p-values consistently above the 0.01 threshold across all test categories. Our architecture implements a distinctive two-tier encryption mechanism, where each layer independently utilizes the Qi hyperchaotic map to generate unique encryption parameters, ensuring template-specific encryption patterns that significantly enhance resistance against chosen-plaintext attacks. Implementation and testing were conducted using MATLAB software. Rigorous security analysis reveals outstanding cryptographic metrics: entropy values exceeding 7.99 bits, an expansive key space of 10320, negligible correlation coefficients (< 10-2), and robust differential attack resistance with Number of Pixels Change Rate (NPCR) of 99.6% and Unified Average Changing Intensity (UACI) of 33.45%. Empirical evaluation conducted on standard CASIA face and iris databases demonstrates practical computational efficiency, achieving average encryption times of 0.630551 seconds per template for 252x252 images size. The framework's superior plaintext sensitivity, coupled with its comprehensive resistance to various cryptographic attacks, positions it as a viable solution for high-security biometric applications. Our findings contribute to the advancement of biometric template protection methodologies, offering a balanced approach between security robustness and operational efficiency in real-world deployment scenarios.