State Observer System Based on K-Means Clustering Machine Learning Model for Cyber-Security of Industrial Network

Machine learning is a good reasoning automated mechanism to help human intelligence to detect potential risks. There are the following ways used techniques could be implemented: spam detection based on the texts analysis, anomalies detection and data prediction. In this paper it'll be discussed the text analysis algorithm based on the clustering machine learning technique for detecting potential area of threaten messages in the modeled industrial system. It is implemented a discrete-time observer algorithm of machine learning model for cybersecurity of industrial network.