An event correlation approach for fault diagnosis in SCADA infrastructures

Supervisory Control and Data Acquisition (SCADA) systems control and monitor industrial and critical infrastructure functions, including gas, water, electricity, and railway. Despite a huge effort from research communities and industries have been made in addressing the dependability of SCADA systems, the diagnosis of SCADA malfunctions is still a challenging issue today. This paper proposes a Simple Event Correlator engine for diagnosis of malfunctions in SCADA systems based on a rule-based event correlation approach. In particular, it is used to detect and filter "relevant" symptoms useful for fault diagnosis in a SCADA infrastructure.