Bayesian Trust Prediction and EASI (Energy Accumulation with Swarm Intelligence) Routing Protocol for Securing WSN

Trust has obtained increased attention in recent years mainly due to the serious impacts of the malicious nodes. Further the leakage of data and the selling of huge data occurs very frequently. The paper proposed a robust method for the prediction of threat prediction by considering the organizational, technical and human factors. The risk prediction for all the authorized users within the WSNwere analysed for the identification of threat risk. With increased application, research towards the extension and optimization of network lifetime has been acclaimed. Energy effectiveness is also a critical factor because of the weakness of the energy source in the sensor nodes. The proposed swarm intelligence-based routing protocol hence aimed to improve the QoS parameters within network. The method is relying upon the chain-based routing method of the EASI (ENERGY ACCUMULATION WITH SWARM INTELLIGENCE) to achieve a distinguished chain. The key aspect of the initiated system is the combination of gathering technique with EASI for the reduction of data redundancy, transmission delay and neighbor node distance linked with lengthy links and the engagement of cluster head (CH) selection technique. The simulation results depicted that the proposed method is far superior to the existing method in terms of packet delivery ratio, through put, energy consumption, and security analysis and delay time.