Secure multimodal biometric authentication using cyclically coupled fractional-order hyperchaotic systems

Abstract This paper presents a secure multimodal biometric authentication framework based on cyclically coupled fractional-order hyperchaotic systems. The features of the face, iris and thumbprint are extracted using classical image descriptors and embedded as initial conditions of coupled hyperchaotic oscillators, transforming biometric authentication into a dynamic process driven by synchronization. The cyclic coupling topology enforces mutual dependency among biometric modalities, ensuring reliable authentication only when all traits originate from the same individual. Numerical analyses based on bifurcation diagrams and Lyapunov exponent spectra confirm the hyperchaotic behavior of the proposed system. Synchronization error analysis demonstrates robust convergence under appropriate coupling strengths, with fractional-order dynamics providing improved stability and faster convergence compared to integer-order counterparts. In addition, chaotic encryption produces noise-like, visually unrecognizable biometric templates, ensuring non-invertibility and template revocability. The proposed framework offers a secure and flexible solution for next-generation multimodal biometric authentication systems.