Abstract

In this paper, research develop a method for identifying abnormal behavior based on two inputs: the trustworthiness of the user, as well as the reliability of the recommendations that they make. Specifically, research look at the reliability of the user recommendations. The next thing that needs to be done is to calculate the node general trust value in order to determine if there has been any kind of malicious attack. This will show whether or not the node has been compromised in any way. It is conceivable that this could lessen the amount of power that is needed for the communication that takes place between different networks. Additionally, it demonstrates that the model is better able to utilize the evaluation results of the common neighbor nodes to synthesize the confidence value when fewer nodes are deployed in the network. This is demonstrated by the fact that fewer nodes are deployed in the network. The reliability of the trust assessment improves while the number of trusts for which recommendations are made decreases.