Control aware techniques for protection of industrial control system

It is very challenging to secure industrial control systems from malwares and protect the system under control. Recent malwares have been specifically targeting public infrastructures like power grids/plants. Protecting against these malwares is challenging as they are configured with deep knowledge of the controller and system under control. Industrial plants are complex systems and hence needs a wholesome approach for attack detection and subsequent protection. Established diagnostic and monitoring algorithms based on sequential analysis techniques like SPRT, CUSUM, and GLR etc., are promising to be used for detection of anomalies. Data mining techniques used for streaming data may also be used for protecting and securing control systems. In this paper, we describe such control aware techniques for protecting the industrial control system. We also present data stream analysis along with simulation result for four tank model.