Data-driven methods, such as deep learning, are widely adopted to detect cyberattacks for
Industrial control systems (ICSs). Due to the neglect of entity spatial relationships (ESR) …

Industrial Control Systems (ICSs) are widely used in critical infrastructures to support the
essential services of society. Therefore, their protection against terrorist activities, natural …

Currently, most anomaly detection approaches in industrial control systems (ICSs) use
network event logs to build models, and current unsupervised machine learning methods …

A method referred to as PbNN is proposed to detect cyber-physical attacks through the
identification of resulting anomalies in the process dynamics of the underlying ICS. Unlike …

Modern Industrial Control Systems (ICS) represent a wide variety of networked infrastructure
connected to physical world. Depending on the application, these control systems are …

Abstract Deep Neural Networks are emerging as effective techniques to detect sophisticated
cyber-attacks targeting Industrial Control Systems (ICSs). In general, these techniques focus …

Industrial Control Systems (ICS) are used to control physical processes in critical
infrastructure. These systems are used in a wide variety of operations such as water …

Industrial Control Systems (ICSs) were initially designed to be operated in an isolated
network. However, recently, ICSs have been increasingly connected to the Internet to …

In recent years, several schemes have been proposed to detect anomalies and attacks on
Cyber-Physical Systems (CPSs) such as Industrial Control Systems (ICSs). Based on the …

As attack techniques become more sophisticated, detecting new and advanced cyberattacks
with traditional intrusion detection techniques based on signature and anomaly is becoming …