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Avoiding detection on twitter: embedding strategies for linguistic steganography

Abstract:

Any serious steganography system should make use of coding. Here, we investigate the performance of our prior linguistic steganographic method for tweets, combined with perfect coding. We propose distortion measures for linguistic steganography, the first of their kind, and investigate the best embedding strategy for the steganographer. These distortion measures are tested with fully automatically generated stego objects, as well as stego tweets filtered by a human operator. We also observed ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
Publisher:
Society of Photo-optical Instrumentation Engineers Publisher's website
Host title:
ISandT International Symposium on Electronic Imaging 2016: Media Watermarking, Security, and Forensics
Publication date:
2016-01-01
ISSN:
0277-786X
Pubs id:
pubs:602188
UUID:
uuid:893731ab-6c38-447b-ab97-d3f555c4ccd7
Local pid:
pubs:602188
Source identifiers:
602188
Deposit date:
2016-02-13

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