Since wireless sensor networks (WSNs) have the requirements of high security and energy conservation, a distributed secure lowenergy routing protocol (SLERP) based on dynamic trust awareness and load balancing is proposed. In order to reduce the adverse influence of malicious nodes in the network, the Chebyshev neural network is used to predict the dynamic trust degree of network nodes to accelerate the speed and accuracy of malicious node detection. Based on the comprehensive consideration of the average dynamic trust degree of cluster-head nodes, the load of the cluster-head node, network energy consumption, network lifetime, and accurate route evaluation model are established by the analytic hierarchy process (AHP).Thesearch methods of secure low-energy routing and chromosome crossing and the mutation method are designed based on the genetic algorithm (GA), so as to quickly establish the optimal cluster-head node-set and the optimal routing path of each node. Simulation results show that SLERP can significantly improve the detection speed and detection success rate of malicious nodes, reduce the network energy consumption and load, and effectively extend the network lifetime.
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