A false data injection attack (FDIA) is the main attack method that threatens the security of smart grids. FDIAs mislead the control center to make wrong judgments by modifying the measurement data of the power grid system. Therefore, the effective and accurate detection...
The false data injection attack is emerging as a dangerous cyber-attack for smart grid since it can bypass traditional bad data detection mechanisms and cause erroneous estimation on system states. To accurately detect such a devastating attack, we propose a statistical FDI attacks detection approach...
False Data Injection (FDI) is one of the most dangerous attacks on cyber-physical systems as it could lead to disastrous consequences in the operation of the power grids. In this paper, a comprehensive investigation of the (FDI) attacks in smart grids is presented. A detection algorithm is ...
Locational Detection of False Data Injection Attack in Smart Grid: a Multi-label Classification Approach - arbab-ml/WSYCUHK_FDIA
Detection of false data injection attacks in smart grid: A secure federated deep learning approach. IEEE Trans. Smart Grid 13, 4862–4872 (2022). Article Google Scholar Deng, L., Abdel-Hamid, O. & Yu, D. A deep convolutional neural network using heterogeneous pooling for trading acoustic ...
Li, Y., Wei, X., Li, Y., Dong, Z. & Shahidehpour, M. Detection of false data injection attacks in smart grid: A secure federated deep learning approach.IEEE Trans. Smart Grid13, 4862–4872 (2022). ArticleGoogle Scholar Mahaur, B. & Mishra, K. Small-object detection based on yo...
Robust Detection of False Data Injection Attacks for the Data Aggregation in Internet of Things based Environmental Surveillance Data aggregation is a significant technology for Internet of Things (IoT) based environmental surveillance to compress the redundant data collected from th... L Yang,D Chao,...
DC microgrids are vulnerable to intentional cyber-attacks. Therefore, in this paper, a robust cyber-attack detection scheme is proposed for DC microgrid systems. Utilizing the parity-based method, a multi-objective optimization problem is formulated to achieve robust detection against electrical paramete...
Detection of stealthy attacks on alternating current (AC) static state estimation through false data injection is considered in this paper. To detect the presence of such cyber attacks, we follow a statistical outlier detection approach using a recently proposed machine learning technique called density...
One such attack is false data injection (FDI) [236–239]. Generally, FDI attacks inject malicious packets with the goal of creating small measurement errors that corrupt the component of the smart grid that performs state estimation. To overcome this problem, He et al. [236] used Conditional...