Machine learning for intrusion detection in industrial control systems: Applications, challenges, and recommendations
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 …
Such methods focus on two major areas: detection of intrusions at the network level using …
Machine learning for cybersecurity in smart grids: A comprehensive review-based study on methods, solutions, and prospects
Abstract In modern Smart Grids (SGs) ruled by advanced computing and networking
technologies, condition monitoring relies on secure cyberphysical connectivity. Due to this …
technologies, condition monitoring relies on secure cyberphysical connectivity. Due to this …
Detecting cyberattacks using anomaly detection in industrial control systems: A federated learning approach
In recent years, the rapid development and wide application of advanced technologies have
profoundly impacted industrial manufacturing, leading to smart manufacturing (SM) …
profoundly impacted industrial manufacturing, leading to smart manufacturing (SM) …
Data-driven monitoring and safety control of industrial cyber-physical systems: Basics and beyond
Industrial cyber-physical systems (ICPSs) are the backbones of Industry 4.0 and as such,
have become a core transdisciplinary area of research, both in industry and academia. New …
have become a core transdisciplinary area of research, both in industry and academia. New …
A novel approach for accurate detection of the DDoS attacks in SDN-based SCADA systems based on deep recurrent neural networks
Abstract Supervisory Control and Data Acquisition (SCADA) systems supervise and monitor
critical infrastructures and industrial processes. However, SCADA systems running on …
critical infrastructures and industrial processes. However, SCADA systems running on …
Detection of power grid disturbances and cyber-attacks based on machine learning
Modern intelligent power grid provides an efficient way of managing energy supply and
consumption while facing numerous security threats at the same time. Both natural and man …
consumption while facing numerous security threats at the same time. Both natural and man …
Enhancing IIoT networks protection: A robust security model for attack detection in Internet Industrial Control Systems
Abstract Industrial Internet of Things (IIoT) networks involves heterogeneous technological
and manufacturing services and devices. The communication and data exchange …
and manufacturing services and devices. The communication and data exchange …
Assessing and augmenting SCADA cyber security: A survey of techniques
SCADA systems monitor and control critical infrastructures of national importance such as
power generation and distribution, water supply, transportation networks, and manufacturing …
power generation and distribution, water supply, transportation networks, and manufacturing …
Intrusion detection of industrial internet-of-things based on reconstructed graph neural networks
Industrial Internet-of-Things (IIoT) are highly vulnerable to cyber-attacks due to their open
deployment in unattended environments. Intrusion detection is an efficient solution to …
deployment in unattended environments. Intrusion detection is an efficient solution to …
An integrated framework for privacy-preserving based anomaly detection for cyber-physical systems
M Keshk, E Sitnikova, N Moustafa… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Protecting Cyber-physical Systems (CPSs) is highly important for preserving sensitive
information and detecting cyber threats. Developing a robust privacy-preserving anomaly …
information and detecting cyber threats. Developing a robust privacy-preserving anomaly …