IEEE

Robust Few-Shot Malware Detection in IoT via Adversarial Contrastive Learning on Heterogeneous Behavior Graphs

Abstract: The proliferation of IoT devices has expanded the attack surface for sophisticated, polymorphic malware. Traditional Intrusion Detection Systems (IDS) and standard Graph Neural Networks ...
IEEE

Understand and Detect: Lithographic Hotspot Detection by the Interpretable Graph Attention Network

Abstract: Lithography hotspot detection plays a crucial role in the design-for-manufacturing (DFM) process. Recent developments in machine learning have demonstrated significant advantages in ...