Detection of Intrusion in Wireless Sensor Networks Using AI Approach

We were able to solve the problem of discovering K-barriers with interpretability concerns for use in intrusion detection by collecting data from wireless sensor networks. This gave us the information we needed to find a solution. This paper contains the solution that we came up with. As a result of the results of the suggested model in the paper being assertive and interpretable in this context, vital information pertaining to the matter that was being researched could be gathered. The results were obtained through the process of showing how the model can be interpreted. The challenge is trying to figure out how many barriers are required for adequate territorial defense. It is therefore possible to bring the expenses involved with anticipating and installing equipment in these regions down to a level that is more tolerable. The approach that has been offered provides a fresh perspective on the nature of the underlying issue behavior and is expected to be of assistance in the distribution of relevant data and discoveries. Constructing expert systems that are relevant to the subject matter is doable if one makes use of these fuzzy principles.