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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 …
Review of cyberattack implementation, detection, and mitigation methods in cyber-physical systems
With the rapid proliferation of cyber-physical systems (CPSs) in various sectors, including
critical infrastructure, transportation, healthcare, and the energy industry, there is a pressing …
critical infrastructure, transportation, healthcare, and the energy industry, there is a pressing …
Blockchain and federated learning-based intrusion detection approaches for edge-enabled industrial IoT networks: A survey
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 …
[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) …
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 …
[HTML][HTML] Dependable intrusion detection system using deep convolutional neural network: A novel framework and performance evaluation approach
Intrusion detection systems (IDS) play a critical role in safeguarding computer networks
against unauthorized access and malicious activities. However, traditional IDS approaches …
against unauthorized access and malicious activities. However, traditional IDS approaches …
[HTML][HTML] 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 …
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 …
[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 …
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 …