An event correlation approach for fault diagnosis in SCADA infrastructures

Supervisory Control and Data Acquisition (SCADA) sys- tems control and monitor industrial and critical infrastruc- ture functions, including gas, water, electricity, and railway. Despite a huge effort from research communities and in- dustries 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 Sim- ple Event Correlator engine for diagnosis of malfunctions in SCADA systems based on a rule-based event correlation ap- proach. In particular, it is used to detect and filter “relevant” symptoms useful for fault diagnosis in a SCADA infrastruc- ture.