Federated Learning Based Distributed Localization of False Data Injection Attacks on Smart Grids
Data analysis and monitoring on smart grids are jeopardized by attacks on cyber-physical
systems. False data injection attack (FDIA) is one of the classes of those attacks that target …
systems. False data injection attack (FDIA) is one of the classes of those attacks that target …
Online location-based detection of false data injection attacks in smart grid using deep learning
The smart grid is a multi-dimensional data-generating cyber-physical system. Distributed
architectures and the heterogeneous nature of the Internet-of-Things (IoT) sensors make it …
architectures and the heterogeneous nature of the Internet-of-Things (IoT) sensors make it …
Detection of false data injection attacks in smart grid: A secure federated deep learning approach
As an important cyber-physical system (CPS), smart grid is highly vulnerable to cyber
attacks. Amongst various types of attacks, false data injection attack (FDIA) proves to be one …
attacks. Amongst various types of attacks, false data injection attack (FDIA) proves to be one …
Network Decomposition Based Online Localization and State Recovery for False Data Injection Attacks in Smart Grid
H Yang, X Yi, F Guo, Y Zhang… - 2024 IEEE 19th …, 2024 - ieeexplore.ieee.org
Most existing countermeasure works formulate the detection of false data inject (FDI) attacks
as a typical binary classification problem, which, however, could not be able to localize and …
as a typical binary classification problem, which, however, could not be able to localize and …
Joint detection and localization of stealth false data injection attacks in smart grids using graph neural networks
False data injection attacks (FDIA) are a main category of cyber-attacks threatening the
security of power systems. Contrary to the detection of these attacks, less attention has been …
security of power systems. Contrary to the detection of these attacks, less attention has been …
Detecting false data injection attacks in smart grids: A semi-supervised deep learning approach
The dependence on advanced information and communication technology increases the
vulnerability in smart grids under cyber-attacks. Recent research on unobservable false data …
vulnerability in smart grids under cyber-attacks. Recent research on unobservable false data …
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 …
essential. State estimation-based solutions provide a critical tool in monitoring and control of …
Privacy-preserving federated learning for detecting false data injection attacks on power system
False data injection attacks (FDIA) against power system state estimation have been well
studied due to its potential threat to real-time energy management. However, the existing …
studied due to its potential threat to real-time energy management. However, the existing …
Detection of False Data Injection Attacks in Smart Grid Based on Machine Learning
L Xu, X Li, Y Sun - Advances in Artificial Intelligence and Security: 7th …, 2021 - Springer
The false injection attack on the internal state estimation module of the smart grid energy
management system enables the attackers to forge false power, voltage and topology …
management system enables the attackers to forge false power, voltage and topology …
A locational false data injection attack detection method in smart grid based on adversarial variational autoencoders
Y Wang, Y Zhou, J Ma - Applied Soft Computing, 2024 - Elsevier
Abstract Stealthy FDIA (False Data Injection Attack) is a serious cyber threat that can modify
state estimation of smart grid through maliciously altering the measurement data, but can't …
state estimation of smart grid through maliciously altering the measurement data, but can't …