Machine learning model for managing the insider attacks in big data

In order to formalize information and knowledge about people, devices, applications, and services in the network system, this study provided a model for displaying large data and insider threats. The work’s contribution relates to the further advancement of information security theory and practices. extending the types of characteristics needed to identify insiders In order to tackle the issue of insider identification in a huge quantity of data and identify insiders to obtain the greatest performance indicators, a novel way for integrating two classes of algorithms based on expert rules and machine learning methods is given. By enhancing the techniques, models, and algorithms for identifying CN insiders, the obtained findings demonstrate a relative improvement in the security of the chosen computer Network System (NS). employing big data processing and machine learning techniques on 2.1%.