Securing industrial control systems: components, cyber threats, and machine learning-driven defense strategies
Industrial Control Systems (ICS), which include Supervisory Control and Data Acquisition
(SCADA) systems, Distributed Control Systems (DCS), and Programmable Logic Controllers …
(SCADA) systems, Distributed Control Systems (DCS), and Programmable Logic Controllers …
A comprehensive survey of deep transfer learning for anomaly detection in industrial time series: Methods, applications, and directions
Automating the monitoring of industrial processes has the potential to enhance efficiency
and optimize quality by promptly detecting abnormal events and thus facilitating timely …
and optimize quality by promptly detecting abnormal events and thus facilitating timely …
Fast anomaly identification based on multiaspect data streams for intelligent intrusion detection toward secure industry 4.0
Various cyber attacks often occur in logistics network of the Industry 4.0, which poses a
threat to Internet security. Intrusion detection can intelligently detect anomalous activities …
threat to Internet security. Intrusion detection can intelligently detect anomalous activities …
Federated transfer learning for authentication and privacy preservation using novel supportive twin delayed DDPG (S-TD3) algorithm for IIoT
S Maurya, S Joseph, A Asokan, AA Algethami… - Sensors, 2021 - mdpi.com
The Industrial Internet of Things (IIoT) has led to the growth and expansion of various new
opportunities in the new Industrial Transformation. There have been notable challenges …
opportunities in the new Industrial Transformation. There have been notable challenges …
VANET network traffic anomaly detection using GRU-based deep learning model
The rise of Vehicular Ad-hoc Networks (VANETs) has led to the growing significance in
intelligent transportation systems. This research suggests a deep learning model for …
intelligent transportation systems. This research suggests a deep learning model for …
[HTML][HTML] Res-TranBiLSTM: An intelligent approach for intrusion detection in the Internet of Things
S Wang, W Xu, Y Liu - Computer Networks, 2023 - Elsevier
Abstract The Internet of Things (IoT), as the information carrier of the Internet and
telecommunications networks, is a new network technology comprising physical entities …
telecommunications networks, is a new network technology comprising physical entities …
DDoS attacks in Industrial IoT: A survey
S Chaudhary, PK Mishra - Computer Networks, 2023 - Elsevier
As the IoT expands its influence, its effect is becoming macroscopic and pervasive. One of
the most discernible effects is in the industries where it is known as Industrial IoT (IIoT). IIoT …
the most discernible effects is in the industries where it is known as Industrial IoT (IIoT). IIoT …
A self-attention integrated spatiotemporal LSTM approach to edge-radar echo extrapolation in the Internet of Radars
In recent years, the number of weather-related disasters significantly increases across the
world. As a typical example, short-range extreme precipitation can cause severe flooding …
world. As a typical example, short-range extreme precipitation can cause severe flooding …
Hybrid honey badger-world cup algorithm-based deep learning for malicious intrusion detection in industrial control systems
The security analysis has become the hotspot concern in Industrial Control Systems (ICSs)
that grabs the research attention in today's era. Owing to the rapid admittance of the …
that grabs the research attention in today's era. Owing to the rapid admittance of the …
A conditional GAN-based approach for enhancing transfer learning performance in few-shot HCR tasks
Supervised learning with the restriction of a few existing training samples is called Few-Shot
Learning. FSL is a subarea that puts deep learning performance in a gap, as building robust …
Learning. FSL is a subarea that puts deep learning performance in a gap, as building robust …