A comprehensive review of cyber-attacks and defense mechanisms for improving security in smart grid energy systems: Past, present and future

M Ghiasi, T Niknam, Z Wang, M Mehrandezh… - Electric Power Systems …, 2023 - Elsevier
Due to the advancement in communication networks, metering and smart control systems,
as well as the prevalent use of Internet-based structures, new forms of power systems have …

[HTML][HTML] Securing modern power systems: Implementing comprehensive strategies to enhance resilience and reliability against cyber-attacks

S Abdelkader, J Amissah, S Kinga, G Mugerwa… - Results in …, 2024 - Elsevier
Recent technological advancements in the energy sector, such as the proliferation of electric
vehicles, and smart power electronic devices, have substantially increased the demand for …

LESSON: Multi-label adversarial false data injection attack for deep learning locational detection

J Tian, C Shen, B Wang, X **a… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Deep learning methods can not only detect false data injection attacks (FDIA) but also locate
attacks of FDIA. Although adversarial false data injection attacks (AFDIA) based on deep …

Joint adversarial example and false data injection attacks for state estimation in power systems

J Tian, B Wang, Z Wang, K Cao, J Li… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Although state estimation using a bad data detector (BDD) is a key procedure employed in
power systems, the detector is vulnerable to false data injection attacks (FDIAs). Substantial …

Exploring targeted and stealthy false data injection attacks via adversarial machine learning

J Tian, B Wang, J Li, Z Wang, B Ma… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
State estimation methods used in cyber–physical systems (CPSs), such as smart grid, are
vulnerable to false data injection attacks (FDIAs). Although substantial deep learning …

Intrusion detection model using gene expression programming to optimize parameters of convolutional neural network for energy internet

D Song, X Yuan, Q Li, J Zhang, M Sun, X Fu… - Applied Soft …, 2023 - Elsevier
The open, interconnected, and shared operational characteristics of the energy Internet
introduce more sophisticated cybersecurity attacks. How to accurately detect these cyber …

Datadriven false data injection attacks against cyber-physical power systems

J Tian, B Wang, J Li, C Konstantinou - Computers & Security, 2022 - Elsevier
Power systems are accelerating towards the transition to cyber-physical power systems
(CPPS). Such CPPS include myriads of sensors that generate huge amounts of data. The …

Adversarial attack and defense methods for neural network based state estimation in smart grid

J Tian, B Wang, J Li… - IET Renewable Power …, 2022 - Wiley Online Library
Deep learning has been recently used in safety‐critical cyber‐physical systems (CPS) such
as the smart grid. The security assessment of such learning‐based methods within CPS …

False-data-injection-enabled network parameter modifications in power systems: Attack and detection

C Liu, W He, R Deng, YC Tian… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Due to the close relevance to the reliability and efficiency of power systems, network
parameters such as branch admittance have been the target of various cyberattacks …

[HTML][HTML] Extended kernel Risk-Sensitive loss unscented Kalman filter based robust dynamic state estimation

W Ma, X Kou, J Zhao, B Chen - International Journal of Electrical Power & …, 2023 - Elsevier
The traditional unscented Kalman filter (UKF) with mean square error (MSE) criterion for
dynamic state estimation (DSE) is sensitive for unknown non-Gaussian noise and outliers …