Detecting fingerprinted data in TLS traffic

Konstantin Böttinger, Dieter Schuster, Claudia Eckert

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

We present a new method for detecting known data in certain TLS encrypted communication channels. Our approach enables us to detect single files in eavesdropped TLS secured network traffic. We generate fingerprints by a fine-grained measurement of the entropy of fragments of known data and introduce the application of methods from the field of machine learning to the problem of file detection. We implement all proposed methods on a real data base and show the practical efficiency of our approach.

Original languageEnglish
Title of host publicationASIACCS 2015 - Proceedings of the 10th ACM Symposium on Information, Computer and Communications Security
PublisherAssociation for Computing Machinery
Pages633-638
Number of pages6
ISBN (Electronic)9781450332453
DOIs
StatePublished - 14 Apr 2015
Externally publishedYes
Event10th ACM Symposium on Information, Computer and Communications Security, ASIACCS 2015 - Singapore, Singapore
Duration: 14 Apr 201517 Apr 2015

Publication series

NameASIACCS 2015 - Proceedings of the 10th ACM Symposium on Information, Computer and Communications Security

Conference

Conference10th ACM Symposium on Information, Computer and Communications Security, ASIACCS 2015
Country/TerritorySingapore
CitySingapore
Period14/04/1517/04/15

Keywords

  • Machine Learning
  • TLS
  • Traffic Analysis

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