Patch-based Defenses against Web Fingerprinting Attacks
Shawn Shan, Arjun Nitin Bhagoji, Hai-Tao Zheng, Ben Y. Zhao
Abstract
Anonymity systems like Tor are vulnerable to Website Fingerprinting (WF) attacks, where a local passive eavesdropper infers the victim's activity. WF attacks based on deep learning classifiers have successfully overcome numerous defenses. While recent defenses leveraging adversarial examples offer promise, these adversarial examples can only be computed after the network session has concluded, thus offering users little protection in practical settings.
Topics & Concepts
Adversarial systemAnonymityComputer scienceComputer securitySession (web analytics)Internet privacyArtificial intelligenceWorld Wide WebInternet Traffic Analysis and Secure E-votingAdversarial Robustness in Machine LearningNetwork Security and Intrusion Detection