A comprehensive survey on the cyber-security of smart grids: Cyber-attacks, detection, countermeasure techniques, and future directions
One of the significant challenges that smart grid networks face is cyber-security. Several
studies have been conducted to highlight those security challenges. However, the majority …
studies have been conducted to highlight those security challenges. However, the majority …
Machine learning in industrial control system (ICS) security: current landscape, opportunities and challenges
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 …
and processes, particularly on Industrial Control Systems (ICS). These systems are …
[HTML][HTML] An ensemble deep learning model for cyber threat hunting in industrial internet of things
By the emergence of the fourth industrial revolution, interconnected devices and sensors
generate large-scale, dynamic, and inharmonious data in Industrial Internet of Things (IIoT) …
generate large-scale, dynamic, and inharmonious data in Industrial Internet of Things (IIoT) …
[PDF][PDF] Hybrid Grey Wolf and Dipper Throated Optimization inNetwork Intrusion Detection Systems
The Internet of Things (IoT) is a modern approach that enables connection with a wide
variety of devices remotely. Due to the resource constraints and open nature of IoT nodes …
variety of devices remotely. Due to the resource constraints and open nature of IoT nodes …
Light-weight federated learning-based anomaly detection for time-series data in industrial control systems
With the emergence of the Industrial Internet of Things (IIoT), potential threats to smart
manufacturing systems are increasingly becoming challenging, causing severe damage to …
manufacturing systems are increasingly becoming challenging, causing severe damage to …
A performance overview of machine learning-based defense strategies for advanced persistent threats in industrial control systems
Cybersecurity incident response is a very crucial part of the cybersecurity management
system. Adversaries emerge and evolve with new cybersecurity tactics, techniques, and …
system. Adversaries emerge and evolve with new cybersecurity tactics, techniques, and …
Blockchain and federated learning-based intrusion detection approaches for edge-enabled industrial IoT networks: A survey
S Ali, Q Li, A Yousafzai - Ad Hoc Networks, 2024 - Elsevier
The industrial internet of things (IIoT) is an evolutionary extension of the traditional Internet of
Things (IoT) into processes and machines for applications in the industrial sector. The IIoT …
Things (IoT) into processes and machines for applications in the industrial sector. The IIoT …
Optimization Enabled Deep Learning‐Based DDoS Attack Detection in Cloud Computing
S Balasubramaniam, C Vijesh Joe… - … Journal of Intelligent …, 2023 - Wiley Online Library
Cloud computing is a vast revolution in information technology (IT) that inhibits scalable and
virtualized sources to end users with low infrastructure cost and maintenance. They also …
virtualized sources to end users with low infrastructure cost and maintenance. They also …
Securing industrial internet of things against botnet attacks using hybrid deep learning approach
Industrial Internet of Things (IIoT) formation of a richer ecosystem of intelligent,
interconnected devices while enabling new levels of digital innovation has transformed and …
interconnected devices while enabling new levels of digital innovation has transformed and …
Intrusion detection in iot using deep learning
AM Banaamah, I Ahmad - Sensors, 2022 - mdpi.com
Cybersecurity has been widely used in various applications, such as intelligent industrial
systems, homes, personal devices, and cars, and has led to innovative developments that …
systems, homes, personal devices, and cars, and has led to innovative developments that …