Feature Selection for Website Fingerprinting-Reference-Cited by-同舟云学术

Feature Selection for Website Fingerprinting

Published:2018-08-29 Issue:4 Volume:2018 Page:200-219
ISSN:2299-0984
Container-title:Proceedings on Privacy Enhancing Technologies
language:en
Short-container-title:

Author:

Yan Junhua¹,Kaur Jasleen¹

Affiliation:

1. UNC Chapel Hill

Abstract

Abstract Website fingerprinting based on TCP/IP headers is of significant relevance to several Internet entities. Prior work has focused only on a limited set of features, and does not help understand the extents of fingerprint-ability. We address this by conducting an exhaustive feature analysis within eight different communication scenarios. Our analysis helps reveal several previously-unknown features in several scenarios, that can be used to fingerprint websites with much higher accuracy than previously demonstrated. This work helps the community better understand the extents of learnability (and vulnerability) from TCP/IP headers.

Publisher

Walter de Gruyter GmbH

Subject

General Medicine

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