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InfoResearchPeer-reviewed

Data-Efficient Cross-Domain Few-Shot Website Fingerprinting With Unsupervised Domain Adaptation

Source
IEEE Xplore (Security & AI Journals)(opens in a new tab)
Published
Record updated

Summary

Researchers present UDA-WF, a few-shot website fingerprinting method that uses unsupervised domain adaptation to identify Tor-encrypted websites across domains. It cuts auxiliary data requirements by 95% and pre-training time by 99% versus SOTA methods, reaching 97.37% accuracy in the 20-shot closed-world setting. The method also reaches above 92% and 94% accuracy on the DF and Wang datasets and is reported as more resilient to concept drift and robust to WF defense.