Entropy–Trust–Causality Driven Secure Routing Framework For Adversarial Network Environments Using Quantum Inspired Path Optimization And Digital Twin Validation In Practical Scenarios

Abstract

As communication infrastructure modernizes, including IoT, cyber-physical systems, and high-volume distributed systems, they continue to be targeted by advanced forms of attacks that impact how routing takes place, affect the integrity of trust relationships, and negatively influence network reliability. Therefore, there is an urgent need for secure routing paradigms that are adaptable, and analytically proven to work across changing topologies and stealthy malicious nodes, especially given the limitations of current routing paradigms to account for topology level changes, evolving patterns of malicious behavior, and propagation characteristics of malicious traffic. In addition, many of the existing secure routing frameworks do not include integrated validation frameworks that are able to trace causality of an attack and evaluate the resilience of a routing paradigm under controlled simulation of adversarial conditions. To meet this challenge, a multi-phase framework for secure routing in adversarial network environments is presented. The framework begins with AGEP-NET, the Adversarial Graph Entropy Profiling Network, that models network communication as time-dependent entropy-based graphs to determine abnormal interaction of nodes; the structure formed from the graph processing is used in MATPRS, the Multi-Agent Trust Propagation Reinforcement System, to allow routers to cooperatively use reinforcement learning to develop trust relationships. Following the development of the trust relationships, CATDM, the Causal Adversarial Traffic Decomposition Model, determines causal linkages of malicious traffic propagations. Then QSPOE, the Quantum Inspired Secure Path Optimization Engine, develops candidate routing paths based upon the probability of each path being explored. Finally, DTANS, the Digital Twin Adversarial Network Simulator, tests the resilience of routing paradigms against different types of attack. Overall, the proposed framework enhances the ability to detect adversaries, increases routing reliability and improves overall network resiliency. These improvements provide a solid foundation for the development of future secure routing paradigms for Next Generation distributed systems and adversarial communication environments.