A comprehensive review of cyber-attacks and defense mechanisms for improving security in smart grid energy systems: Past, present and future
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 …
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
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 …
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
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 …
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
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 …
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 …
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 …
introduce more sophisticated cybersecurity attacks. How to accurately detect these cyber …
Datadriven false data injection attacks against cyber-physical power systems
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 …
(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 …
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
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 …
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
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 …
dynamic state estimation (DSE) is sensitive for unknown non-Gaussian noise and outliers …