Methods from machine learning are used in the design of secure Industrial Control Systems.
Such methods focus on two major areas: detection of intrusions at the network level using …

The advent of Industry 4.0 has led to a rapid increase in cyber attacks on industrial systems
and processes, particularly on Industrial Control Systems (ICS). These systems are …

The challenge faced by industrial control systems is that they are vulnerable to adversarial
sample attacks. In the ICS field, the challenge with adversarial sample attacks is that the …

Anomaly-based intrusion detection promises to detect novel or unknown attacks on
industrial control systems by modeling expected system behavior and raising corresponding …

Detection of cyber‐threats in the smart grid Supervisory Control and Data Acquisition
(SCADA) is still remains one of the complex and essential processes need to be highly …

In recent years, Industrial Control Systems (ICS) have been targeted through a range of
cyber-attacks that attempt to infiltrate and disrupt process controls of industrial control …

Cyber-Physical Systems (CPS) have gained popularity due to the increased requirements
on their uninterrupted connectivity and process automation. Due to their connectivity over …

With the increasing prevalence of machine learning and its application in Intrusion Detection
Systems (IDSs) for Cyber Physical Systems (CPSs), where safety and reliability are critical …

Cyber-physical systems (CPSs) are complex interconnections of control systems that
operate in tandem to carry out industrial processes and activities. A research problem of …

Internet of Things (IoT) devices are becoming increasingly ubiquitous in our lives, from
personal health monitoring to house and factory management. Further, IoT devices are …