With the rapid development of the information and communication technology in DC
microgrids (DCmGs), the threat of deception attacks has been widely recognized. However …

Aiming at a cleaner future power system, many regimes in the world have proposed their
ambitious decarbonizing plan, with increasing penetration of renewable energy sources …

Industrial Control Systems (ICSs) rely on Programmable Logic Controllers (PLCs) to operate
within a set of states. The states are composed of variables that determine how sensor data …

Anomaly detection in multivariate time series has been widely studied in one-class
classification (OCC) setting. The training samples in this setting are assumed to be normal …

The watermarking method, which adds unique watermarks to data, has been widely used for
integrity attack detection in industrial control systems (ICSs). Existing literature generally …

Data is a critical asset in AI, as high-quality datasets can significantly improve the
performance of machine learning models. In safety-critical domains such as autonomous …

The rapid growth of the Internet of Things (IoT) has led to the widespread adoption of the IoT
networks in numerous digital applications. To counter physical threats in these systems …

Recommender systems predict and suggest relevant options to users in various domains,
such as e-commerce, streaming services, and social media. Recently, deep reinforcement …

Kernels are at the heart of modern operating systems, whereas their development comes
with vulnerabilities. Coverage-guided fuzzing has proven to be a promising software testing …

This research presents the optimized adversarial machine learning framework, OptAML,
which is developed for use in water distribution and treatment systems. In consideration of …