Fast detection of advanced persistent threats for smart grids: A deep reinforcement learning approach

S Yu - ICC 2022-IEEE International Conference on …, 2022 - ieeexplore.ieee.org
Data management systems in smart grids have to address advanced persistent threats
(APTs), where malware injection methods are performed by the attacker to launch stealthy …

Defense against advanced persistent threats in smart grids: A reinforcement learning approach

B Ning, L Xiao - 2021 40th Chinese Control Conference (CCC), 2021 - ieeexplore.ieee.org
In smart girds, supervisory control and data acquisition (SCADA) systems have to protect
data from advanced persistent threats (APTs), which exploit vulnerabilities of the power …

Artificial intelligence empowered cyber threat detection and protection for power utilities

K Hasan, S Shetty, S Ullah - 2019 IEEE 5th international …, 2019 - ieeexplore.ieee.org
Cyber threats have increased extensively during the last decade, especially in smart grids.
Cybercriminals have become more sophisticated. Current security controls are not enough …

[HTML][HTML] Multi-layer defense algorithm against deep reinforcement learning-based intruders in smart grids

HM Rouzbahani, H Karimipour, L Lei - … Journal of Electrical Power & Energy …, 2023 - Elsevier
Abstract The Internet of Energy envisions the next generation of smart grids as a highly
interconnected network, including advanced metering infrastructures, distributed energy …

ACapsule Q-learning based reinforcement model for intrusion detection system on smart grid

TT Khoei, N Kaabouch - 2023 IEEE International Conference …, 2023 - ieeexplore.ieee.org
Smart grid is an innovative technology that offers efficiency, low carbon emissions, and high
energy storage. However, this promising technology has several shortcomings, including …

[HTML][HTML] Attention-aware deep reinforcement learning for detecting false data injection attacks in smart grids

R Huang, Y Li, X Wang - International Journal of Electrical Power & Energy …, 2023 - Elsevier
Cyber-attacks have long undermined the security and stable operation of the smart grid. The
increasing share of intermittent energy aggravates the uncertainty of the grid environment …

Intelligent intrusion detection system for smart grid applications

D Mohanty, K Sethi, S Prasath… - … Conference on Cyber …, 2021 - ieeexplore.ieee.org
Smart grid is a cyber-physical system that enhances the capability of conventional power
networks leveraging functional automation of information and communication technologies …

LSTM-Based false data injection attack detection in smart grids

Y Zhao, X Jia, D An, Q Yang - 2020 35th Youth Academic …, 2020 - ieeexplore.ieee.org
As a typical cyber-physical system, smart grid has attracted growing attention due to the safe
and efficient operation. The false data injection attack against energy management system is …

Reinforcement learning-based adaptive feature boosting for smart grid intrusion detection

C Hu, J Yan, X Liu - IEEE Transactions on Smart Grid, 2022 - ieeexplore.ieee.org
Intrusion detection systems (IDSs) are crucial in the security monitoring for the smart grid
with increasing machine-to-machine communications and cyber threats thereafter. However …

On the performance metrics for cyber-physical attack detection in smart grid

SY Diaba, M Shafie-khah, M Elmusrati - Soft Computing, 2022 - Springer
Abstract Supervisory Control and Data Acquisition (SCADA) systems play an important role
in Smart Grid. Though the rapid evolution provides numerous advantages it is one of the …