Results 181 to 190 of about 63,938 (281)

Graph neural network‐based attack prediction for communication‐based train control systems

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
Abstract The Advanced Persistent Threats (APTs) have emerged as one of the key security challenges to industrial control systems. APTs are complex multi‐step attacks, and they are naturally diverse and complex. Therefore, it is important to comprehend the behaviour of APT attackers and anticipate the upcoming attack actions.
Junyi Zhao   +3 more
wiley   +1 more source

Image and video analysis using graph neural network for Internet of Medical Things and computer vision applications

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma   +4 more
wiley   +1 more source

From Distributed Noisy Data to Event‐Triggered Pinning Observer‐Based Control

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT This paper presents an event‐triggered pinning observer‐based control of unknown large‐scale interconnected systems under false data injection attacks using distributed noisy data without any system identification step. An exogenous system is used to model the false data injection attack.
Xuan Jia   +3 more
wiley   +1 more source

A Probability‐Aware AI Framework for Reliable Anti‐Jamming Communication

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Adversarial jamming attacks have increased on communication systems, causing distortion and threatening transmissions. Typical attacks rely on traditional, well‐defined cryptographic protocols and frequency‐hopping techniques. Nevertheless, these techniques become vulnerable when facing intelligent jammers.
Tawfeeq Shawly, Ahmed A. Alsheikhy
wiley   +1 more source

A Review of Human–AI Synergy in Smart Energy Management Concepts, Functions, Applications, and Future Frontiers

open access: yesEnergy Internet, EarlyView.
ABSTRACT Smart energy management systems (EMS) are entering a phase of rapid transformation. Artificial intelligence (AI)—including machine learning (ML), deep learning (DL), and reinforcement learning (RL)—has become the computational backbone for real‐time forecasting, scheduling, and control of renewable‐rich power systems.
Sihai An   +5 more
wiley   +1 more source

Home - About - Disclaimer - Privacy