SATA generates realistic new traffic patterns absent from training data and boosts open-world website fingerprinting accuracy by 90.81% and AUROC by 48.37% through protocol-based semantic augmentation and cross-layer feature alignment.
Classify traffic rather than flow: Versatile multi-flow encrypted traffic classification with flow clustering
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More Than Meets the Eye: A Semantics-Aware Traffic Augmentation Framework for Generalizable Website Fingerprinting
SATA generates realistic new traffic patterns absent from training data and boosts open-world website fingerprinting accuracy by 90.81% and AUROC by 48.37% through protocol-based semantic augmentation and cross-layer feature alignment.