Detecting network based attacks in Industrial Control Systems

Oliver Gunnell


Supervised by Eirini S Anthi; Moderated by Neetesh Saxena

The student will use publicly available datasets from industrial control systems such the Secure Water Treatment (SWaT) Dataset, to build a lightweight intrusion detection system tailored for ICS protocols. These datasets contain not only benign traffic but also malicious, which can be used to build (machine learning based) models that distinguish between the different types of attacks. Other parameters for detecting attacks, such as PLC data, can also be taken into consideration.

Initial Plan (03/02/2020) [Zip Archive]

Final Report (17/05/2020) [Zip Archive]

Publication Form