Clustering algorithms have emerged as an alternative powerful meta-learning tool to
accurately analyze the massive volume of data generated by modern applications. In …

Deploying machine learning (ML)-based intrusion detection systems (IDS) is an effective
way to improve the security of industrial control systems (ICS). However, ML models …

Supervisory Control and Data Acquisition (SCADA) systems face the absence of a protection
technique that can beat different types of intrusions and protect the data from disclosure …

In this article, we propose a real-time anomaly detection framework for an NoC-based many-
core architecture. We assume that processing cores and memories are safe and anomaly is …

Constrained by the high acquisition and labeling cost, traffic data in industrial control
systems (ICSs) are usually extremely imbalanced. Deep-learning-based (DL) industrial …

The occurrence of zero-day attacks in high-speed networks is increasingly common. As most
network intrusions are detrimental to the network via fast-spreading; real-time monitoring …

Abstract Supervisory Control and Data Acquisition (SCADA) systems control and monitor
industrial and critical infrastructure functions, such as electricity, gas, water, waste, railway …

Standard Ethernet (IEEE 802.3 and the TCP/IP protocol suite) is gradually applied in
industrial control system (ICS) with the development of information technology. It breaks the …

Cyber-physical systems are found in production and industrial systems, as well as critical
infrastructures which play a crucial role in our society. The integration of standard computing …

Ever-growing population of people and new electronic gadgets demand huge electricity.
Existing power grids mostly use non-renewable energy sources for electricity generation …