Abstract
Wireless Sensor Networks are generally employed for observing and monitoring specific environments. WSNs are made from a huge amount of low-cost sensor nodes separated and distributed in different environments for distributing data through sensor nodes. The collection of data by the various sensors were transmitted into the Base Station. An enhanced Trust-Based Adaptive Acknowledgment based Intrusion-Detection System was proposed from positive distributions in WSNs. A Kalman filter algorithm is used in Multi-objective Particle Swarm Optimization to predict trust nodes over the WSN. Simulations were carried out for non-malicious (0% malicious) networks, and various ranges of malicious nodes in the network were investigated. The outcomes show that the proposed MPSO achieves an improvement of 3.3% than PSO at 0% malicious nodes concerning the PDR. Similarly, at 30% malicious, the PDR of MPSO achieves better by 3.5% than PSO in WSN.