A NEW METHOD AGAINST ATTACKS ON NETWORKED INDUSTRIAL CONTROL SYSTEMS

Nguyen Dao Truong, Le My Tu



DOI: 10.15625/vap.2016.0002

Abstract


In this paper, by incorporating knowledge of the physical system under control, we proposed the new method to detect computer attacks that change the behavior of the targeted industrial control system. By using knowledge of the physical system we are able to focus on the final objective of the attack, and not on the particular mechanisms of how vulnerabilities are exploited, and how the attack is hidden. We also analyze the safety of our solution by exploring the effects of stealthy attacks, and by hopping that automatic attack-response mechanisms will not drive the system to an unsafe state. In our paper, we proposed two module: one for changing detection by sequential detection and CUSUM statistic, other one for responsing attacks by linear model predictive control algorithm to keep the system in safety state before human operators can control the system.

Keywords


Linear model predictive control, control system, model algorithmic control, dynamic matrix control, attack

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