Dynamic Anomaly Detection with High-fidelity Simulators: A Convex Optimization Approach

The main objective of this article is to develop scalable dynamic anomaly detectors with high-fidelity simulators of power systems. On the one hand, models in high-fidelity simulators are typically 'intractable' if one opts to describe them in a mathematical formulation in order to apply existing model-based approaches from the anomaly...

Training Strategies for Autoencoder-based Detection of False Data Injection Attacks

The security of energy supply in a power grid critically depends on the ability to accurately estimate the state of the system. However, manipulated power flow measurements can potentially hide overloads and bypass the bad data detection scheme to interfere the validity of estimated states. In this paper, we use an autoencoder neural network to...