Entropy-Adaptive Multi-Map Chaotic Modulation for Physical-Layer Security

Abstract

This paper presents a Multi-Map Dynamic-Entropy Intrusion-Aware Chaotic Modulation (MU-DE-IAEACM-MM) framework for adaptive physical-layer security in multi-user wireless systems. Unlike conventional chaos-based schemes that rely on static parameter secrecy, the proposed architecture treats entropy as a regulated security variable and dynamically updates chaotic control parameters using an entropy-driven adaptation law. Heterogeneous chaotic maps, including Logistic, Tent, Chebyshev, and Sine generators, are distributed across users to enlarge entropy dimensionality and reduce cross-user statistical dependence. A correlation-based intrusion metric is incorporated to detect improved adversarial reconstruction coherence and trigger controlled entropy escalation. Stability analysis establishes bounded convergence conditions for the adaptive update process. Monte Carlo simulations under AWGN, fading, impulsive, colored, and narrowband interference demonstrate a persistent BER gap between legitimate and mismatched receivers and measurable secrecy capacity gains over representative fixed-parameter chaotic modulation schemes. The framework maintains positive secrecy rates in dense deployments with up to 64 legitimate users and 30 passive eavesdroppers. The results indicate that entropy-regulated multi-map chaotic modulation provides a scalable and synchronisation-stable approach for adaptive physical-layer security in next-generation wireless and IoT networks.