Artificial Intelligence and Security of Industrial Control Systems

Abstract

Developments, expansions and upgrades in the field of industrial information technology have introduced a large number of new threats to industries. This real-time data demonstrates whether additional attention to system is needed and requirements in terms of resources, performance, or improvements are being met. Cyber threat actors have become exceptionally skilled at infiltrating their victim targets. Industrial Control Systems (ICS) are also recognized as attractive targets for threat actors. While these networks were generally thought to be more secure due to lack of connection to outside world of the corporate network or on the internet, now it is not the same case and attackers have managed to compromise them and steal valuable production data. Additionally, mechanical control can be undertaken or compromised, centrifugation can be dynamically rearranged or devices can be reprogrammed in order to accelerate or slow down ICS operations post such specialized attacks. This may result in total industrial equipment being destroyed or permanently damaged, or also may endanger personnel’s life who is working at the ICS site. This chapter surveys about the latest research and methodologies undertaken for measuring and managing industrial cyber threats risks, and talks about a dearth of industrial-control-system-specific security metrics that has been identified as a barrier to implementing these methodologies. Some of the most effective tools in combating these threats are the emerging techniques in Artificial Intelligence. By combining these threats with real-time data monitoring along with orchestration and automated response, AI analytics solutions are proving their best possible desirable outcome when compared to legacy systems and human-intervention driven response times.