A method for automatic identification of signatures of steganography software

Authors:
Graeme Bell;Yeuan-Kuen Lee
Affiliations:
School of Information Technology, Murdoch University, Perth, WA;Department of CSIE, Ming Chuan University, Gueishan, Taiwan
Venue:
IEEE Transactions on Information Forensics and Security
Year:
2010

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Abstract

A fully automated, blind, media-type agnostic approach to steganalysis is presented here. Steganography may sometimes be exposed by detecting automatically characterized regularities in output media caused by weak implementations of steganography algorithms. Fast and accurate detection of steganography is demonstrated experimentally here across a range of media types and a variety of steganography approaches.