Minimizing Embedding Impact for H.264 Steganography by Progressive Trellis Coding

This paper proposes a novel coding strategy to achieve distortion minimization for H.264 steganography with quantized discrete cosine transform (QDCT) coefficients. Currently, with the help of syndrome-trellis codes (STCs), state-of-the-art image steganography embeds messages while minimizing a heuristically defined distortion function. However, this concept cannot be directly ported to steganography using compressed video as the cover media. According to the intra prediction principle, an H.264 QDCT coefficient block is predicted and coded based on previously encoded blocks, so even a slight embedding change will set off a chain reaction in the remaining cover blocks. Considering the cover block dependency, we make necessary changes to the standard trellis coding structure so as to be applicable for the joint compression embedding scenario. During the coding/embedding procedure, we maintain multiple contexts corresponding to possible optimal routes, and retrace each route periodically to determine how each cover block should be modified. After each modification, the remaining cover blocks, as well as their embedding costs, are re-evaluated, and each context is updated to reflect the embedding effect. In this way, the global optimality can be approached progressively in a block-by-block manner, so our proposed method is named progressive trellis coding (PTC). Extensive experiments have been conducted, and corresponding results show that the adoption of PTC brings about a significant gain in embedding performance.

[1]  Jessica J. Fridrich,et al.  Minimizing Additive Distortion in Steganography Using Syndrome-Trellis Codes , 2011, IEEE Transactions on Information Forensics and Security.

[2]  Yun Q. Shi,et al.  An efficient JPEG steganographic scheme using uniform embedding , 2012, 2012 IEEE International Workshop on Information Forensics and Security (WIFS).

[3]  Jessica J. Fridrich,et al.  Minimizing embedding impact in steganography using trellis-coded quantization , 2010, Electronic Imaging.

[4]  Xianfeng Zhao,et al.  Cover Block Decoupling for Content-Adaptive H.264 Steganography , 2018, IH&MMSec.

[5]  Xiaojing Ma,et al.  A Data Hiding Algorithm for H.264/AVC Video Streams Without Intra-Frame Distortion Drift , 2010, IEEE Transactions on Circuits and Systems for Video Technology.

[6]  Tomás Pevný,et al.  Using High-Dimensional Image Models to Perform Highly Undetectable Steganography , 2010, Information Hiding.

[7]  Rainer Böhme,et al.  On the Statistical Properties of Syndrome Trellis Coding , 2017, IWDW.

[8]  Jessica J. Fridrich,et al.  Designing steganographic distortion using directional filters , 2012, 2012 IEEE International Workshop on Information Forensics and Security (WIFS).

[9]  Jessica J. Fridrich,et al.  Gibbs Construction in Steganography , 2010, IEEE Transactions on Information Forensics and Security.

[10]  Yuesheng Zhu,et al.  A Controllable Error-Drift Elimination Scheme for Watermarking Algorithm in H.264/AVC Stream , 2011, IEEE Signal Processing Letters.

[11]  Bin Li,et al.  A new cost function for spatial image steganography , 2014, 2014 IEEE International Conference on Image Processing (ICIP).

[12]  Jessica J. Fridrich,et al.  Multivariate gaussian model for designing additive distortion for steganography , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

[13]  Tomás Pevný,et al.  Exploring Non-Additive Distortion in Steganography , 2018, IH&MMSec.

[14]  Rainer Böhme,et al.  Moving steganography and steganalysis from the laboratory into the real world , 2013, IH&MMSec '13.

[15]  Loren Merritt,et al.  X264: A HIGH PERFORMANCE H.264/AVC ENCODER , 2006 .

[16]  Xianfeng Zhao,et al.  A Steganalytic Algorithm to Detect DCT-based Data Hiding Methods for H.264/AVC Videos , 2017, IH&MMSec.

[17]  Jessica J. Fridrich,et al.  Universal distortion function for steganography in an arbitrary domain , 2014, EURASIP Journal on Information Security.

[18]  Zafar Shahid,et al.  Considering the reconstruction loop for data hiding of intra- and inter-frames of H.264/AVC , 2013, Signal Image Video Process..

[19]  Kuo-Liang Chung,et al.  An improved DCT-based perturbation scheme for high capacity data hiding in H.264/AVC intra frames , 2013, J. Syst. Softw..

[20]  Jiwu Huang,et al.  Adaptive steganalysis against WOW embedding algorithm , 2014, IH&MMSec '14.

[21]  Lai-Man Po,et al.  A novel watermarking scheme with compensation in bit-stream domain for H.264/AVC , 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.

[22]  Jessica J. Fridrich,et al.  Improving Steganographic Security by Synchronizing the Selection Channel , 2015, IH&MMSec.

[23]  Jessica J. Fridrich,et al.  Selection-channel-aware rich model for Steganalysis of digital images , 2014, 2014 IEEE International Workshop on Information Forensics and Security (WIFS).

[24]  Ji-Sang Yoo,et al.  The problems in digital watermarking into intra-frames of H.264/AVC , 2010, Image Vis. Comput..

[25]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[26]  Weiming Zhang,et al.  Near-Optimal Codes for Information Embedding in Gray-Scale Signals , 2010, IEEE Transactions on Information Theory.

[27]  Jessica J. Fridrich,et al.  Low-Complexity Features for JPEG Steganalysis Using Undecimated DCT , 2015, IEEE Transactions on Information Forensics and Security.

[28]  Jessica J. Fridrich,et al.  Rich Models for Steganalysis of Digital Images , 2012, IEEE Transactions on Information Forensics and Security.

[29]  Bin Li,et al.  A Strategy of Clustering Modification Directions in Spatial Image Steganography , 2015, IEEE Transactions on Information Forensics and Security.

[30]  Ajay Luthra,et al.  Overview of the H.264/AVC video coding standard , 2003, IEEE Trans. Circuits Syst. Video Technol..