Few-Shot Website Fingerprinting Attack with Data Augmentation

This work introduces a novel data augmentation method for few-shot website fingerprinting (WF) attack where only a handful of training samples per website are available for deep learning model optimization. Moving beyond earlier WF methods relying on manually-engineered feature representations, more...

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Bibliographic Details
Main Authors: Mantun Chen, Yongjun Wang, Zhiquan Qin, Xiatian Zhu
Format: Article
Language:English
Published: Hindawi-Wiley 2021-01-01
Series:Security and Communication Networks
Online Access:http://dx.doi.org/10.1155/2021/2840289