"[RCF] Enhancing Few-shot Website Fingerprinting via Supervised Contrastive Learning and Ensemble Late-Fusion"
Abstract
"This dataset and code repository supports the experiments in the paper \u201cEnhancing Few-shot Website Fingerprinting via Supervised Contrastive Learning and Ensemble Late-Fusion.\u201d The dataset contains network traffic traces collected under controlled Tor browsing scenarios, along with preprocessing scripts and experimental pipelines. The provided source code implements data loading utilities, supervised contrastive training, and ensemble late-fusion evaluation for website fingerprinting classifiers. As the code was originally developed and tested within the authors' experimental environment, minor adjustments may be required to adapt it to different system configurations. These resources aim to facilitate reproducible research on few-shot website fingerprinting and encrypted traffic analysis."
Fields of Study & Subjects
Internet Traffic Analysis and Secure E-voting
Privacy-Preserving Technologies in Data
Privacy
Security
and Data Protection
Publication details
- Journal / source
- IEEE DataPort
- Publication date
- 5 March 2026
- Language
- EN
- Document type
- Dataset