The classifier judged this item not relevant to AI security, so it is left out of lists, feeds, the API and dataset releases. If that is wrong, report a correction on this page.
InfoResearchPeer-reviewed
Early-Stage Detection of Encrypted Malware Traffic via Multi-Flow Temporal Graph Learning
- Published
- Record updated
Summary
DawnGuard is a framework for detecting encrypted malware traffic from the earliest stage of an attack, using multi-flow temporal graph learning. It applies a self-adjusting data augmentation strategy to early-stage traffic, builds Multi-Flow Graph Features (MGF), and feeds them to a Vision Transformer-based detector. Tested on two real-world datasets, it achieves an average F1 of 95.11%, 8.7% higher than the state-of-the-art method, using only the first 20% loading ratio of complete traffic.