Writing on wet paper

Fridrich, Jessica; Goljan, Miroslav; Lisonĕk, P; Soukal, David

doi:10.1109/tsp.2005.855393

Cited by 220 publications

(105 citation statements)

References 22 publications

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“…Aly [3] chose the candidate MVs according to their associated prediction errors. By applying mature coding techniques such as wet paper codes (WPCs) [13] and syndrome-trellis codes (STCs) [14,15] to video steganography, adaptive steganographic schemes have been presented in recent years. In Yao et al 's work [4], an adaptive MV-based steganography was proposed by considering the statistical distribution change and the prediction error change.…”

Section: Introductionmentioning

confidence: 99%

“…In [5], Cao et al exploited the opportunity to optimize the ME perturbation using the loss caused by video compression process. The data embedding was implemented using a double-layered (first channel: STCs [15]; second channel: WPCs [13]) coding structure with distortion scale calculated on optimal neighbors. In Wang et al 's work [6], data was embedded based on the distortion defined by considering motion characteristic of video content, MVs local optimality, and statistical distribution.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Segmentation Based Video Steganalysis to Detect Motion Vector Modification

Wang

Cao

Zhao

2017

Security and Communication Networks

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This paper presents a steganalytic approach against video steganography which modifies motion vector (MV) in content adaptive manner. Current video steganalytic schemes extract features from fixed-length frames of the whole video and do not take advantage of the content diversity. Consequently, the effectiveness of the steganalytic feature is influenced by video content and the problem of cover source mismatch also affects the steganalytic performance. The goal of this paper is to propose a steganalytic method which can suppress the differences of statistical characteristics caused by video content. The given video is segmented to subsequences according to block's motion in every frame. The steganalytic features extracted from each category of subsequences with close motion intensity are used to build one classifier. The final steganalytic result can be obtained by fusing the results of weighted classifiers. The experimental results have demonstrated that our method can effectively improve the performance of video steganalysis, especially for videos of low bitrate and low embedding ratio.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Segmentation Based Video Steganalysis to Detect Motion Vector Modification

Wang

Cao

Zhao

2017

Security and Communication Networks

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“…There are some embedding methods, e.g., quantization index modulation (QIM) [17]- [21], dither modulation (DM) [22], and wet paper code [23]. Wet paper code [23] is a method in which embedding positions can be selected from a binary bit sequence arbitrarily and no one needs to know the positions in decoding.…”

Section: Introductionmentioning

confidence: 99%

“…Wet paper code [23] is a method in which embedding positions can be selected from a binary bit sequence arbitrarily and no one needs to know the positions in decoding.…”

Section: Introductionmentioning

confidence: 99%

Method of Spread Spectrum Watermarking Using Quantization Index Modulation for Cropped Images

Yamamoto

Kawamura

2015

IEICE Trans. Inf. & Syst.

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SUMMARYWe propose a method of spread spectrum digital watermarking with quantization index modulation (QIM) and evaluate the method on the basis of IHC evaluation criteria. The spread spectrum technique can make watermarks robust by using spread codes. Since watermarks can have redundancy, messages can be decoded from a degraded stego-image. Under IHC evaluation criteria, it is necessary to decode the messages without the original image. To do so, we propose a method in which watermarks are generated by using the spread spectrum technique and are embedded by QIM. QIM is an embedding method that can decode without an original image. The IHC evaluation criteria include JPEG compression and cropping as attacks. JPEG compression is lossy compression. Therefore, errors occur in watermarks. Since watermarks in stego-images are out of synchronization due to cropping, the position of embedded watermarks may be unclear. Detecting this position is needed while decoding. Therefore, both error correction and synchronization are required for digital watermarking methods. As countermeasures against cropping, the original image is divided into segments to embed watermarks. Moreover, each segment is divided into 8 × 8 pixel blocks. A watermark is embedded into a DCT coefficient in a block by QIM. To synchronize in decoding, the proposed method uses the correlation between watermarks and spread codes. After synchronization, watermarks are extracted by QIM, and then, messages are estimated from the watermarks. The proposed method was evaluated on the basis of the IHC evaluation criteria. The PSNR had to be higher than 30 dB. Ten 1920 × 1080 rectangular regions were cropped from each stego-image, and 200-bit messages were decoded from these regions. Their BERs were calculated to assess the tolerance. As a result, the BERs were less than 1.0%, and the average PSNR was 46.70 dB. Therefore, our method achieved a high image quality when using the IHC evaluation criteria. In addition, the proposed method was also evaluated by using StirMark 4.0. As a result, we found that our method has robustness for not only JPEG compression and cropping but also additional noise and Gaussian filtering. Moreover, the method has an advantage in that detection time is small since the synchronization is processed in 8 × 8 pixel blocks.

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“…For instance, modifications on less textured areas of image will be easily detected by steganalysis. To solve this problem, Fridrich et al proposed wet paper codes [12], in which the cover elements are divided into two parts, wet elements and dry elements. By wet paper codes, the sender can embed messages by only modifying dry elements and the receiver can extract the message without any knowledge on the positions of dry elements.…”

Section: Introductionmentioning

confidence: 99%

Defining embedding distortion for motion vector-based video steganography

Yao

Zhang

et al. 2014

Multimed Tools Appl

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This paper presents an effective methodology for motion vector-based video steganography. The main principle is to design a suitable distortion function expressing the embedding impact on motion vectors by exploiting the spatial-temporal correlation based on the framework of minimal-distortion steganography. Two factors are considered in the proposed distortion function, which are the statistical distribution change (SDC) of motion vectors in spatial-temporal domain and the prediction error change (PEC) caused by modifying the motion vectors. The practical embedding algorithm is implemented using syndrome-trellis codes (STCs). Experimental results show that the proposed method can enhance the security performance significantly compared with other existing motion vectorbased video steganographic approaches, while obtaining the higher video coding quality as well.

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Writing on wet paper

Cited by 220 publications

References 22 publications

Segmentation Based Video Steganalysis to Detect Motion Vector Modification

Segmentation Based Video Steganalysis to Detect Motion Vector Modification

Method of Spread Spectrum Watermarking Using Quantization Index Modulation for Cropped Images

Defining embedding distortion for motion vector-based video steganography

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