Intrusion Detection Using Random Naives Bayes Classifier In Smart Grids

Smart grids (SG) represent succeeding step in modernizing this electrical grid. The communications network is combined with the Smart grid so as to collect data that may be used to increase the potency of the grid, reduce power consumption, and improve the reliability of services, among different varied benefits. Smart Grid communication networks are distinctive in their giant scale. . The Wireless networks in communication setting are going to be exposed to several threats, in order that SGDIDS can realize attacks using Random Forest Naives Bayes Classifier. Random Forest Naives Bayes is trained using information that's relevant to their level and additionally improves detection. This paper proposes a FPGA primarily based network intrusion detection in communication network of smart Grid to detect and classify malicious data and possible cyber attacks.