[HTML][HTML] Learning-based methods for cyber attacks detection in IoT systems: A survey on methods, analysis, and future prospects

U Inayat, MF Zia, S Mahmood, HM Khalid… - Electronics, 2022 - mdpi.com
Internet of Things (IoT) is a develo** technology that provides the simplicity and benefits of
exchanging data with other devices using the cloud or wireless networks. However, the …

Smart substation communications and cybersecurity: A comprehensive survey

J Gaspar, T Cruz, CT Lam… - … communications surveys & …, 2023 - ieeexplore.ieee.org
Electrical grids generate, transport, distribute and deliver electrical power to consumers
through a complex Critical Infrastructure which progressively shifted from an air-gaped to a …

Machine learning approach using artificial neural networks to detect malicious nodes in IoT networks

KKS Liyakat - International Conference on Machine Learning, IoT …, 2023 - Springer
Devices can now effortlessly and wirelessly share data with one another over the internet or
other networked systems thanks to a relatively new technology called Internet of Things …

Detecting malicious nodes in IoT networks using machine learning and artificial neural networks

KKS Liyakat - … Conference on Emerging Smart Computing and …, 2023 - ieeexplore.ieee.org
Thanks to a relatively new technology known as the Internet of Things, devices can now
easily and wirelessly share data with one another over the internet or other networked …

WAMS operations in power grids: A track fusion-based mixture density estimation-driven grid resilient approach toward cyberattacks

HM Khalid, MM Qasaymeh, SM Muyeen… - IEEE Systems …, 2023 - ieeexplore.ieee.org
Synchrophasor-based wide-area monitoring system (WAMS) applications are vital for
acquiring the real-time grid information under ambient and nonlinear conditions. The high …

Graph-based detection for false data injection attacks in power grid

X Li, Y Wang, Z Lu - Energy, 2023 - Elsevier
False data injection attack (FDIA) is the main network attack type threatening power system.
FDIA affect the accuracy of data by modifying the measured values of measuring equipment …

[HTML][HTML] Network threat detection using machine/deep learning in sdn-based platforms: a comprehensive analysis of state-of-the-art solutions, discussion, challenges …

N Ahmed, A Ngadi, JM Sharif, S Hussain, M Uddin… - Sensors, 2022 - mdpi.com
A revolution in network technology has been ushered in by software defined networking
(SDN), which makes it possible to control the network from a central location and provides …

A deep learning-based attack detection mechanism against potential cascading failure induced by load redistribution attacks

A Khaleghi, MS Ghazizadeh… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The occurrence of load redistribution (LR) attacks has disastrous consequences for the
power system, but these attacks have a significant impact when they cause cascading …

[HTML][HTML] Wide area monitoring system operations in modern power grids: A median regression function-based state estimation approach towards cyber attacks

HM Khalid, F Flitti, MS Mahmoud, MM Hamdan… - … Energy, Grids and …, 2023 - Elsevier
Modern power grid is a generation mix of conventional generation facilities and variable
renewable energy resources (VRES). The complexity of such a power grid with generation …

A data mining/ANFIS and adaptive control for detection and mitigation of attacks on DC MGs

A Abazari, M Zadsar, M Ghafouri… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The integration of information and communication technologies (ICTs) has provided modern
smart grids, such as direct current (DC) microgrids (MGs), with various advantages, eg, the …