Steganography using Gibbs random fields
Proceedings of the 12th ACM workshop on Multimedia and security
Gibbs construction in steganography
IEEE Transactions on Information Forensics and Security
On dangers of overtraining steganography to incomplete cover model
Proceedings of the thirteenth ACM multimedia workshop on Multimedia and security
Steganalysis of DCT-embedding based adaptive steganography and YASS
Proceedings of the thirteenth ACM multimedia workshop on Multimedia and security
"Break our steganographic system": the ins and outs of organizing BOSS
IH'11 Proceedings of the 13th international conference on Information hiding
Ensuring message embedding in wet paper steganography
IMACC'11 Proceedings of the 13th IMA international conference on Cryptography and Coding
Batch steganography in the real world
Proceedings of the on Multimedia and security
Adaptive image data hiding in edges using patched reference table and pair-wise embedding technique
Information Sciences: an International Journal
Digital image steganography using universal distortion
Proceedings of the first ACM workshop on Information hiding and multimedia security
Distortion function designing for JPEG steganography with uncompressed side-image
Proceedings of the first ACM workshop on Information hiding and multimedia security
Moving steganography and steganalysis from the laboratory into the real world
Proceedings of the first ACM workshop on Information hiding and multimedia security
Secret sharing with multi-cover adaptive steganography
Information Sciences: an International Journal
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This paper proposes a complete practical methodology for minimizing additive distortion in steganography with general (nonbinary) embedding operation. Let every possible value of every stego element be assigned a scalar expressing the distortion of an embedding change done by replacing the cover element by this value. The total distortion is assumed to be a sum of per-element distortions. Both the payload-limited sender (minimizing the total distortion while embedding a fixed payload) and the distortion-limited sender (maximizing the payload while introducing a fixed total distortion) are considered. Without any loss of performance, the nonbinary case is decomposed into several binary cases by replacing individual bits in cover elements. The binary case is approached using a novel syndrome-coding scheme based on dual convolutional codes equipped with the Viterbi algorithm. This fast and very versatile solution achieves state-of-the-art results in steganographic applications while having linear time and space complexity w.r.t. the number of cover elements. We report extensive experimental results for a large set of relative payloads and for different distortion profiles, including the wet paper channel. Practical merit of this approach is validated by constructing and testing adaptive embedding schemes for digital images in raster and transform domains. Most current coding schemes used in steganography (matrix embedding, wet paper codes, etc.) and many new ones can be implemented using this framework.