This study proposes a secure routing planning algorithm that integrates an improved Dempster-Shafer Evidence Theory (D-S ET) and enhanced Multi-Objective Ant Colony Optimization (MOACO) to balance security protection and Energy Consumption (EC) in Wireless Sensor Networks (WSN). For the D-S ET, we correct third-party recommendation bias by calculating evidence distance and introducing discount coefficients, thereby optimizing its conflict handling mechanism, solving the problem of node credibility misjudgment caused by traditional evidence fusion, and achieving accurate Node Trust Evaluation (NTE) through a direct and indirect dual trust mechanism. For MOACO, we integrated elite retention strategy, improved crowding distance, and mutation convergence operation to optimize the Pareto optimal solution set, improving the search accuracy and stability of the algorithm, and achieving multi-objective routing optimization with node trust value and remaining energy as the core objectives. Based on a 100 node WSN simulation environment, the algorithm was compared with typical baseline methods under consistent initial parameter settings. The experimental results show that when the proportion of Malicious Nodes (MN) is 25%, the detection rate of MN in this algorithm is 84.5%, and the false positive rate is 9.2%, which is better than the comparative methods. In terms of routing performance, it extends the lifecycle of WSN to 937 rounds, maintaining a stable throughput of 4344 bps and a minimum average delay of 33 ms. Without black hole attacks, the MN is only 37.5 J. Faced with 10 single type black hole attack nodes, its MN decreases by 4.8%, and the packet loss rate is controlled at 9.9%, demonstrating excellent anti-attack performance. This algorithm effectively balances the security and energy efficiency of WSN, and innovative improvements to the core algorithm provide reliable technical support for the efficient and stable operation of WSN, with significant practical application value.
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