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Detection of steganographic techniques on Twitter

Abstract:
We propose a method to detect hidden data in English text. We target a system previously thought secure, which hides messages in tweets. The method brings ideas from image steganalysis into the linguistic domain, including the training of a feature-rich model for detection. To identify Twitter users guilty of steganography, we aggregate evidence; a first, in any do- main. We test our system on a set of 1M steganographic tweets, and show it to be effective.
Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Oxford college:
Worcester College
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Oxford college:
University College
Role:
Author
Publisher:
Association for Computational Linguistics Publisher's website
Volume:
2015
Pages:
2564–2569
Host title:
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing
Publication date:
2015-01-01
ISBN:
9781941643327
Language:
English
Keywords:
Subjects:
UUID:
uuid:ab678459-e414-4819-86d0-d5ae8dcfd370
Local pid:
ora:12237
Deposit date:
2015-09-09

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