Cybersecurity is increasingly vital in power systems, particularly with the rise of Internet of Things (IoT) devices. The integration of these devices amplifies the system’s exposure to threats like False Data Injection Attacks (FDIA). This work proposes a Generative Adversarial Networks (GANs) framework for generating FDIA against power system state estimation from the attacker’s perspective. Spe...Show More
False data injection (FDI) attacks can bypass bad data detection and mislead state estimation (SE), resulting in economic losses and security issues. Existing FDI attacks consider the spatial correlation without considering the temporal correlations. Therefore, FDI attacks can correctly mislead the traditional Weighted Least Square SE (WLS-SE) with desired voltage incremental, but hard to accurate...Show More
In a wide range of classification tasks, training data will produce class-imbalance due to collection difficulties in some classes, which leads to prediction biases on minority classes. For the class-imbalanced problem, existing researches are usually based on the assumption that the training dataset and the test dataset are from similar distributions. In reality, both of the datasets often come f...Show More
