"[RCF] Enhancing Few-shot Website Fingerprinting via Supervised Contrastive Learning and Ensemble Late-Fusion"

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Authors: Zhaoxin Jin
Cited by: 0

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