Cyber attacks analysis and mitigation with machine learning techniques in ICS SCADA systems

Supervisory control and data acquisition (SCADA) system is a computer based system implemented to control the physical processes which enhances the operational efficiency, cost reduction and energy consumption. It supervises physical process by collecting data from sensors and performs monitoring, data logging, alarm and diagnostic functions. The advancement in technology for connectivity in communication protocols has resulted the system to be more vulnerable to cyber-attacks. The classifications of various attacks along with the intrusions detection methods have been highlighted. Mitigation techniques such as honeypot simulation which helps in vulnerability assessment, along with machine learning algorithms, suitable for intrusion detection and prevention of cyber-attacks in SCADA systems has been detailed