Securing SCADA Systems Using Machine Learning

Abstract

SCADA systems are used to effectively monitor and control critical industrial infrastructure . Due to Industry 4.0 , SCADA systems have evolved towards linked architectures, which has enhanced operational efficiency but also made them more vulnerable to cyberattacks. SCADA systems, which were once intended to be dependable, are now at risk from malware, DoS attacks, illegal access,and various types of threats endangering both safety and service continuity. In this context, artificial intelligence enables real-time detection of anomalies and cyberattacks especially by ML and deep DL based IDS. This paper offers a thorough analysis of current AI strategies for SCADA security, emphasising important techniques, difficulties, and results .