Trust aware secure routing with optimal energy efficiency and performance enhancement in mobile adhoc networks

This study addresses critical security vulnerabilities, energy constraints, and dynamic topology issues in mobile ad-hoc networks (MANETs). The primary goal is to develop a trust-aware secure routing protocol that isolates malicious node attacks while optimizing energy efficiency and quality of service (QoS) parameters during data transmission. Utilizing a wireless network traffic dataset, a novel routing framework was developed and executed using Python. The proposed technique dynamically computes multi-attribute node trust, reputation, and residual energy. It balances secure encryption with adaptive multi-hop path selection to drop malicious entities and distribute the network load. Simulation results show that the Proposed Technique achieves a peak packet delivery ratio of 92 %, trust accuracy of 95 %, and throughput efficiency of 95 %. It significantly outperforms existing benchmarks (AODV, LEACH, BPNN, SMC, CNN, and PSO), sustaining a high trust level of 92 and expanding node stability to 90 while optimizing energy consumption to 88 %. The proposed protocol provides a highly reliable, energy-efficient routing structure that extends network lifetime and minimizes latency in resource-constrained environments. Future work will integrate advanced machine learning models for dynamic threat forecasting and real-time adaptive flow control in large-scale MANET deployments.