earticle

영어

With advanced internet of things (IoT) and cloud/edge computing, industrial control systems (ICSs) are evolving. However, there are critical concerns and challenges about the cybersecurity of the IoT-enabled ICSs against cyber-attacks. To reduce the risk of cyber-attacks, an intrusion detection system (IDS) is required. In general, IDS utilizes signature-based or behavior-based methods to detect potential harmful anomalies. In this paper, we propose a hybrid intrusion detection approach deploying a statistical filtering method and a composite autoencoder to effectively detect anomalous behaviors caused by cyber-attacks. The proposed method is validated by experimental data acquired from a real water treatment system as a case study of cyberattack on ICSs.