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Modern Supervisory Control and Data Acquisition SCADA systems used by theelectric utility industry to monitor and control electric power generation,transmission and distribution are recognized today as critical components ofthe electric power delivery infrastructure. SCADA systems are large, complexand incorporate increasing numbers of widely distributed components. Thepresence of a real time intrusion detection mechanism, which can cope withdifferent types of attacks, is of great importance, in order to defend a systemagainst cyber attacks This defense mechanism must be distributed, cheap andabove all accurate, since false positive alarms, or mistakes regarding theorigin of the intrusion mean severe costs for the system. Recently anintegrated detection mechanism, namely IT-OCSVM was proposed, which isdistributed in a SCADA network as a part of a distributed intrusion detectionsystem (IDS), providing accurate data about the origin and the time of anintrusion. In this paper we also analyze the architecture of the integrateddetection mechanism and we perform extensive simulations based on real cyberattacks in a small SCADA testbed in order to evaluate the performance of theproposed mechanism.

Combining ensemble methods and social network metrics for improving accuracy of OCSVM on intrusion detection in SCADA systems