Engineering Commons^™

Intrusion Detection For Industrial Control Systems, Kurt Lamon

EWU Masters Thesis Collection

Industrial Control Systems (ICS) are rapidly shifting from closed local networks, to remotely accessible networks. This shift has created a need for strong cybersecurity anomaly and intrusion detection for these systems; however, due to the complexity and diversity of ICSs, well defined and reliable anomaly and intrusion detection systems are still being developed. Machine learning approaches for anomaly and intrusion detection on the network level may provide general protection that can be applied to any ICS. This paper explores two machine learning applications for classifying the attack label of the UNSW-NB15 dataset. The UNSW-NB15 is a benchmark dataset that was …