Machine learning for anomaly detection: A systematic review
Anomaly detection has been used for decades to identify and extract anomalous
components from data. Many techniques have been used to detect anomalies. One of the …
components from data. Many techniques have been used to detect anomalies. One of the …
Cybersecurity for industrial control systems: A survey
Abstract Industrial Control System (ICS) is a general term that includes supervisory control &
data acquisition (SCADA) systems, distributed control systems (DCS), and other control …
data acquisition (SCADA) systems, distributed control systems (DCS), and other control …
Machine learning-based intrusion detection for smart grid computing: A survey
Machine learning (ML)-based intrusion detection system (IDS) approaches have been
significantly applied and advanced the state-of-the-art system security and defense …
significantly applied and advanced the state-of-the-art system security and defense …
Anomaly detection for industrial control system based on autoencoder neural network
C Wang, B Wang, H Liu, H Qu - Wireless Communications and …, 2020 - Wiley Online Library
As the Industrial Internet of Things (IIoT) develops rapidly, cloud computing and fog
computing become effective measures to solve some problems, eg, limited computing …
computing become effective measures to solve some problems, eg, limited computing …
Cyber-attacks detection in industrial systems using artificial intelligence-driven methods
Modern industrial systems and critical infrastructures are constantly exposed to malicious
cyber-attacks that are challenging and difficult to identify. Cyber-attacks can cause severe …
cyber-attacks that are challenging and difficult to identify. Cyber-attacks can cause severe …
Design of efficient based artificial intelligence approaches for sustainable of cyber security in smart industrial control system
A Alzahrani, THH Aldhyani - Sustainability, 2023 - mdpi.com
Online food security and industrial environments and sustainability-related industries are
highly confidential and in urgent need for network traffic analysis to attain proper security …
highly confidential and in urgent need for network traffic analysis to attain proper security …
A taxonomy of supervised learning for idss in scada environments
Supervisory Control and Data Acquisition (SCADA) systems play an important role in
monitoring industrial processes such as electric power distribution, transport systems, water …
monitoring industrial processes such as electric power distribution, transport systems, water …
Fault injection analytics: A novel approach to discover failure modes in cloud-computing systems
Cloud computing systems fail in complex and unexpected ways due to unexpected
combinations of events and interactions between hardware and software components. Fault …
combinations of events and interactions between hardware and software components. Fault …
A review of current machine learning approaches for anomaly detection in network traffic
WA Ali, KN Manasa, M Bendechache… - … and the Digital …, 2020 - search.informit.org
Due to the advance in network technologies, the number of network users is growing rapidly,
which leads to the generation of large network traffic data. This large network traffic data is …
which leads to the generation of large network traffic data. This large network traffic data is …
Better safe than sorry: Risk Management based on a safety-augmented Network Intrusion Detection System
Interconnected industrial control system (ICS) networks based on routable protocols are
susceptible to remote attacks similar to classical information technology (IT) networks …
susceptible to remote attacks similar to classical information technology (IT) networks …