Additive manufacturing of soft magnets for electrical machines—A review

TN Lamichhane, L Sethuraman, A Dalagan… - Materials Today …, 2020 - Elsevier
With growing interest in electrification from clean energy technologies, such as wind power,
and use of pure electric powertrains in various applications, the demand for next-generation …

Security of networked control systems subject to deception attacks: A survey

ZH Pang, LZ Fan, H Guo, Y Shi, R Chai… - … Journal of Systems …, 2022 - Taylor & Francis
A networked control system (NCS), which integrates various physical components by
utilising communication networks, is a complex intelligent control system with high flexibility …

A hybrid deep learning model for discrimination of physical disturbance and cyber-attack detection in smart grid

K Bitirgen, ÜB Filik - International Journal of Critical Infrastructure Protection, 2023 - Elsevier
A smart grid (SG) consists of an interconnection of an electrical grid, communication, and
information networks. The rapid developments of SG technologies have resulted in complex …

Survey of machine learning methods for detecting false data injection attacks in power systems

A Sayghe, Y Hu, I Zografopoulos, XR Liu… - IET Smart …, 2020 - Wiley Online Library
Over the last decade, the number of cyber attacks targeting power systems and causing
physical and economic damages has increased rapidly. Among them, false data injection …

Locational detection of the false data injection attack in a smart grid: A multilabel classification approach

S Wang, S Bi, YJA Zhang - IEEE Internet of Things Journal, 2020 - ieeexplore.ieee.org
State estimation is critical to the monitoring and control of smart grids. Recently, the false
data injection attack (FDIA) is emerging as a severe threat to state estimation. Conventional …

Multi-layer intrusion detection system with ExtraTrees feature selection, extreme learning machine ensemble, and softmax aggregation

J Sharma, C Giri, OC Granmo, M Goodwin - EURASIP Journal on …, 2019 - Springer
Recent advances in intrusion detection systems based on machine learning have indeed
outperformed other techniques, but struggle with detecting multiple classes of attacks with …

Deep learning-based multilabel classification for locational detection of false data injection attack in smart grids

D Mukherjee, S Chakraborty, S Ghosh - Electrical Engineering, 2022 - Springer
With the recent advancement in smart grid technology, real-time monitoring of grid is utmost
essential. State estimation-based solutions provide a critical tool in monitoring and control of …

A review on distribution system state estimation uncertainty issues using deep learning approaches

Y Raghuvamsi, K Teeparthi - Renewable and Sustainable Energy Reviews, 2023 - Elsevier
This study highlights the research works on different uncertainty issues encountered in
distribution system state estimation (DSSE). The DSSE plays a crucial role since the …

[HTML][HTML] A review on machine learning techniques for secured cyber-physical systems in smart grid networks

MK Hasan, RA Abdulkadir, S Islam, TR Gadekallu… - Energy Reports, 2024 - Elsevier
The smart grid (SG) is an advanced cyber-physical system (CPS) that integrates power grid
infrastructure with information and communication technologies (ICT). This integration …

Trustiness-based hierarchical decentralized federated learning

Y Li, X Wang, R Sun, X Xie, S Ying, S Ren - Knowledge-Based Systems, 2023 - Elsevier
Federated Learning (FL) breaks the “data island” and lets clients cooperate in training a
shared model with private data locally. And hierarchical framework is used in FL to alleviate …