Wet ZZW construction for steganography

Filler, Tomáš; Fridrich, Jessica

doi:10.1109/wifs.2009.5386467

Cited by 13 publications

(9 citation statements)

References 9 publications

(18 reference statements)

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“…Wet paper codes minimizing the number of changed dry pixels were described in [34], [31], [14], [13].…”

Section: A Prior Artmentioning

confidence: 99%

“…A well-known example is matrix embedding where the sender minimizes the total number of embedding changes. Near-optimal coding schemes for this problem appeared in [8], [9], together with other clever constructions and extensions [10], [11], [12], [13], [14], [15]. When the singleletter distortions vary across the cover elements, reflecting thus different costs of individual embedding changes, current coding methods are highly suboptimal [2], [4].…”

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confidence: 99%

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Minimizing Additive Distortion in Steganography Using Syndrome-Trellis Codes

Filler

Judas

Fridrich

2011

IEEE Trans.Inform.Forensic Secur.

759

440

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Abstract-This paper proposes a complete practical methodology for minimizing additive distortion in steganography with general (non-binary) 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 non-binary case is decomposed into several binary cases by replacing individual bits in cover elements. The binary case is approached using a novel syndromecoding 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.

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“…Wet paper codes minimizing the number of changed dry pixels were described in [34], [31], [14], [13].…”

Section: A Prior Artmentioning

confidence: 99%

mentioning

confidence: 99%

Minimizing Additive Distortion in Steganography Using Syndrome-Trellis Codes

Filler

Judas

Fridrich

2011

IEEE Trans.Inform.Forensic Secur.

759

440

View full text Add to dashboard Cite

show abstract

“…An established way of evaluating practical coding algorithms in steganography is to compare the embedding efficiency e(α) = αn/E π [D] for a fixed expected relative payload α = m/n with the upper bound derived from (4). When the number of changes is minimized, e is the average number of bits hidden per one change.…”

Section: Performance Bounds and Comparison Metricsmentioning

confidence: 99%

“…Special codes, called wet paper codes, were proposed for embedding with wet pixels [4,11] (pixels prohibited to be modified for which I i = {x i }). The recently proposed Syndrome-Trellis Codes (STCs) [7,8] unify the approach, achieve near-optimal performance for various distortion costs ̺ i , and perform well even with a large number of wet pixels.…”

Section: Introductionmentioning

confidence: 99%

Minimizing additive distortion functions with non-binary embedding operation in steganography

Filler

Fridrich

2010

2010 IEEE International Workshop on Information Forensics and Security

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Most practical steganographic algorithms for empirical covers embed messages by minimizing a sum of per-pixel distortions. Current near-optimal codes for this minimization problem [7] are limited to a binary embedding operation. In this paper, we extend this work to embedding operations of larger cardinality. The need for embedding changes of larger amplitude and the merit of this construction are confirmed experimentally by implementing an adaptive embedding algorithm for digital images and comparing its security to other schemes.

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“…15,[20][21][22]. Even though other distortion profiles, such as the linear profile, are of great interest to steganography, no general solution with performance close to the bound is currently known.…”

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confidence: 99%

Minimizing embedding impact in steganography using trellis-coded quantization

2010

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In this paper, we propose a practical approach to minimizing embedding impact in steganography based on syndrome coding and trellis-coded quantization and contrast its performance with bounds derived from appropriate rate-distortion bounds. We assume that each cover element can be assigned a positive scalar expressing the impact of making an embedding change at that element (single-letter distortion). The problem is to embed a given payload with minimal possible average embedding impact. This task, which can be viewed as a generalization of matrix embedding or writing on wet paper, has been approached using heuristic and suboptimal tools in the past. Here, we propose a fast and very versatile solution to this problem that can theoretically achieve performance arbitrarily close to the bound. It is based on syndrome coding using linear convolutional codes with the optimal binary quantizer implemented using the Viterbi algorithm run in the dual domain. The complexity and memory requirements of the embedding algorithm are linear w.r.t. the number of cover elements. For practitioners, we include detailed algorithms for finding good codes and their implementation. Finally, we report extensive experimental results for a large set of relative payloads and for different distortion profiles, including the wet paper channel.

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Wet ZZW construction for steganography

Cited by 13 publications

References 9 publications

Minimizing Additive Distortion in Steganography Using Syndrome-Trellis Codes

Minimizing Additive Distortion in Steganography Using Syndrome-Trellis Codes

Minimizing additive distortion functions with non-binary embedding operation in steganography

Minimizing embedding impact in steganography using trellis-coded quantization

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