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

Abstract 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.