臺灣博碩士論文加值系統

本論文提出藏匿訊息到載體上的隱匿學設計如影像、文字、視訊和音訊藏匿等等。隱匿學於各種不同的應用中可以發現，其中有一些重要的因素如藏匿容量、安全性、複雜度、效能、強健性與可偵測性會被當成設計法則。隱匿學中的主要需求是安全性與嵌入效能，嵌入效能也直接影響到安全性，因此本論文所強調的是藏匿效能的重要性，而且高效能的藏匿機置是需要的。建構具有靠近理論極限的高效能碼是一個大家所討論的問題且有以下兩個主要重點:
(1)嵌入機置需要一個好的結構與夠長的編碼而且此碼還要有好的同位產生矩陣或生成矩陣。
(2)基於第一點，如何得到有效的嵌入計算與編/解碼問題。
一種有效的隱匿技術是矩陣編碼。在本論文中也提出迴旋嵌入碼進行大容量的嵌入。由論文結果可知迴旋碼是滿足上述兩種設計原則而接近理論極限的隱匿學設計方式之一。由籬笆結構和Viterbi演算法所構成的迴旋嵌入碼是適合對於一個夠長的訊息進行編碼，當然此碼也可以適當的調整編碼率。此外迴旋嵌入碼是可以使用最佳編碼矩陣方式進行編碼的一種機置。對於上述設計要求的第二點，我們也提出了兩種次佳化的隱匿學演算法，那是具有不錯的嵌入效能且具低複雜度的方式我們稱之為WAE演算法與LIAE演算法。另外本論文也提出一些新式的浮水印演算法。在浮水印的知情編碼中，目標編碼向量是需要依據載體向量進行修正而獲得失真度與強健性之間的最佳點。在Miller的討論中，我們改善它所提出的隨機向量編碼方式，而改用線性區塊碼當成籬笆結構中的節區編碼向量。使用線性區塊碼的好處是節區中編碼可以簡單的由生成矩陣產生，而線性碼的特性也有好的籬笆結構的空間分割。由區塊碼的特徵，失真度與強健性兩者可以由提出的參數嵌入演算法做改變。最後有三種不同用途的演算法在論文中被提出來如type-1、type-2和type-3演算法。

This dissertation presents the design of steganography for embedding information in cover or host such as images, text, video, and audio. Steganography can be used in a variety of applications. A number of design criteria is
necessary, including payload, security, complexity, performance, robustness, and detectability. The main requirements for a steganographic scheme are security and embedding efficiency. Embedding efficiency directly influences the security; thus, steganography emphasizes embedding efficiency. High embedding efficiency is required for steganographic schemes. Constructing structured codes with an embedding efficiency close to the
theoretical bound is a crucial open problem that involves the following concerns: (1) embedding schemes require structured codes of sufficiently large length that possess an excellent parity-check matrix or generator matrix; (2) structured codes are more computationally efficient and efficient encoding/decoding procedures are developed based on structured codes. One effective steganographic technique involves matrix embedding (ME) codes. Unlike conventional ME codes, the method presented in this study for embedding large payloads employs a family of convolutional codes known as convolutional embedding (CE) codes. The convolutional embedding codes can be used as an alternative to satisfy the two conditions for approaching the theoretical upper bound. The CE codes, developed based on trellis structure and Viterbi decoding, which is a ML algorithm, are suitable for coding with sufficiently large block lengths that increase embedding efficiency and for altering the embedding rate. Additionally, CE codes can directly employ the optimal design of current convolutional codes to obtain the embedding scheme. For the point two of above-mentioned concerns, we also present two suboptimal embedding versions of steganographic scheme, that is, WAE and LIAE algorithm, which achieve better embedding efficiency with low complexity. Moreover, this dissertation also presents some novel embedding algorithm of steganographic schemes over noisy channel (also called watermarking schemes). In informed embedding, the message codeword from informed coding is subsequently modified according to the host signal, attempting to attain an optimal tradeoff between fidelity and robustness in the watermarked image. Instead of using randomly generated reference vectors as arc labels in Miller''s work, this trellis structure was modified by using the codewords of a linear block code to label the arcs in
the trellis. The advantage of using such linear codewords is that the codewords as arc labels can be easily produced by use of a generate matrix than randomly generates reference vectors as arc labels. The characteristic of the block codes is subsequently applied to the trellis partition. By featuring block codes, both the fidelity and robustness can be changed by a number of parameters. Three embedded algorithms are presented in this dissertation, including type-1, type-2, and type-3.

1 CODING WITH SIDE INFORMATION FOR STEGANOGRAPHY APPLICATION 1
1.1 Steganography and CCSI problem 1
1.2 Some important issues in steganography 2
1.3 Outline of dissertation and research contributions 3
2 CODING WITH SIDE INFORMATION SYSTEM AND EMBED-
DING ALGORITHM FOR LINEAR CODES 7
2.1 Coding with side information system 7
2.2 Steganography as communication with side information 8
2.3 Average distance using linear codes for embedding system 11
2.3.1 Binary embedding regarded as binary source coding 11
2.3.2 Average distance to code 14
3 OPTIMAL EMBEDDING ALGORITHM FOR LINEAR CODES 17
3.1 Optimal embedding for linear codes 18
3.2 Binary embedding using convolutional codes 22
3.2.1 Embedding for systematic form 22
3.2.2 Embedding using Systematic convolutional codes 22
3.2.3 CE codes for small payloads 26
3.3 Non-binary convolutional embedding codes 27
3.3.1 Related work 27
3.3.2 Combine (q-1)/2 embedding with q-ary convolutional embedding codes 29
3.4 CE codes use ZZW construction to enhance performance 31
3.5 Simulation results 33
4 STEGANOGRAPHIC SYSTEM USING SUBOPTIMAL EMBEDDING ALGORITHMS 42
4.1 Suboptimal binary embedding algorithm 43
4.2 Weight approximation embedding algorithm, WAE, algorithm 45
4.3 Linear independent approximation embedding, LIAE, algorithm 48
4.3.1 The solution for adaptive matrix embedding 48
4.3.2 Optimal solution for adaptive matrix embedding 48
4.3.3 Suboptimal solution and LIAE algorithm 50
4.4 Simulation results 53
5 STEGANOGRAPHIC SYSTEM OVER NOISY CHANNEL (WA-
TERMARKING) 63
5.1 Introduction 63
5.2 Trellis-based informed embedding 65
5.3 The proposed informed embedding algorithm 67
5.3.1 Informed embedding without memory, type-1 68
5.3.2 Informed embedding with memory, type-2 71
5.3.3 Informed embedding without memory using hamming metric, type-3 73
5.3.4 Detection of message 75
5.4 Simulation results 77
6 CONCLUSIONS 90

[1] F. A. P. Petitcolas, R. J. Anderson, and M. G. Kuhn, ``Information hiding-a survey,'' Proc. IEEE, vol. 87, no. 6, pp. 1062-1078, Jul. 1999.
[2] A. Baros, F. Franco, D. Delannay, and B. Macq, ``Rate-distortion analysis of steganography for conveying stereovision disparity maps,'' Proc. SPIE, vol. 5306, pp. 268-273, Jan. 2004.
[3] M. J. Wainwright, ``Sparse Graph Codes for Side Information and Binning,'' IEEE Signal Process. Mag., vol. 24, no. 5, pp. 47-57, Sep. 2007.
[4] R.G. Gallager. ``Low-Density Parity Check Codes.'' Cambridge, MA: MIT Press, 1963.
[5] J. Fridrich, T. Filler, ``Practical methods for minimizing embedding impact in steganography,'' in Proc, SPIE, Security, Steganography, and Watermarking of
Multimedia, vol. 6050, 2007.
[6] S. Gelfand and M. Pinsker, ``Coding for channel with random parameters,'' Probl, Control Inform. Theory, vol. 9, no. 1, pp. 19-31, Jan. 1980.
[7] J. Fridrich and D. Soukal, ``Matrix embedding for large payloads'' IEEE Trans. Inf. Theory, vol. 1, no. 3, pp. 390-395, Sep. 2006.
[8] R. Crandall. Some notes on steganography. Steganography Mailing List, avail-able from http://os.inf.tu-dresden.de/westfeld/crandall.pdf, 1998.
[9] J. Bierbrauer, On Crandall''s Problem [Online]. Available: http:// www.ws.binghamton.edu/fridrich/covcodes.pdf 1998.
[10] R. Y. M. Li, O. C. Au, K. K. Lai, C. K. M. Yuk, and S.-Y. Lam, ``Data hiding with tree based parity check,'' in Proc. IEEE Int. Conf. Multimedia and Expo (ICME 07), 2007, pp. 635-638.
[11] R. Y. M. Li, O. C. Au, C. K. M. Yuk, S. K. Yip, and S. Y. Lam, ``Halftone Image Data Hiding with Block-Overlapping Parity Check,'' Proc. IEEE, vol. 2, pp. 1930-196, Apr. 2007.
[12] Y. C. Tseng, Y. Y. Chen, and H. K. pan, ``A secure data hiding scheme for binary images,'' IEEE Trans. Commun., vol. 50, no. 8, pp. 1227-1231, Aug.2002.
[13] C. Hou, C. Lu, S. Tsai, and W. Tzeng, ``An optimal data hiding scheme with tree-based parity check,'' IEEE Trans. Image Process., vol. 20, no. 3, pp. 880-886, Mar. 2011.
[14] Jiayong Chen, Yuefei Zhu, Yong Shen and Weiming Zhang, ``Efficient Matrix Embedding Based on Random Linear Codes,'' in Proc. MINES2010, pp. 879-883, Dec. 2010.
[15] Yunkai Gao, Xiaolong Li and Bin Yang, ``Employing optimal matrix for efficient matrix embedding,'' in Proc. IIH-MSP2009, pp.161-165, Sep. 2009.
[16] J.-J. Wang and H. Chen, ``A suboptimal embedding algorithm with low complexity for binary data hiding'', in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), kyoto, Japan, Mar. 2012.
[17] J.-J. Wang, H. Chen, and C.-Y. Lin, ``An adaptive matrix embedding technique for binary hiding with an efficient LIAE algorithm,'' World Scientific and Engineering Academy and Society (WSEAS), vol. 8, issue 2, April 2012.
[18] J.-J.Wang, H. Chen, and C.-Y. Lin, ``A low-complexity matrix embedding technique for grayscale signals,'' An International Journal of Research and Surveys (ICIC-ELB), vol. 3, issue 3, June 2012.
[19] F. Galand and G. Kabatiansky. Information hiding by coverings. In Proceedings ITW2003, Paris, France, 2003, pages 151-154.
[20] W. Zhang, X. Zhang, and S. Wang, ``Maximizing steganographic embedding efficiency by combining hamming codes and wet paper codes," in Proc. Int. Workshop Inf. Hiding (IH 08), 2008, vol. LNCS 5284, pp. 60-71.
[21] J. Fridrich, ``Asymptotic behavior of the ZZW embedding construction,'' IEEE Trans. Inf. Forensics Security, vol. 4, no. 1, pp. 151 154, Mar. 2009.
[22] W. Zhang and X. Wang, ``Generalization of the ZZW embedding construction for steganography,'' IEEE Trans. Inf. Forensics Security, vol. 4, pp. 564-569,
Sep. 2009.
[23] T. Filler and J. Fridrich, ``WET ZZW construction for steganography,'' in IEEE Workshop on Information Forensic and Security (WIFS), London, U.K., Dec. 7-9, 2009.
[24] D. SchÄonfeld and A. Winkler, ``Embedding with syndrome coding based on BCH codes,'' in Proc. ACM 8th Workshop on Multimed. Secur., 2006, pp. 214-223.
[25] J. Bierbrauer and J. Fridrich, ``Constructing good covering codes for applications in steganography,'' LNCS Trans. Data Hiding and Multimed. Secur., vol. 4920, no. 3, pp. 1-22, 2008.
[26] J.-J. Wang, H. Chen, and C.-Y. Lin, ``A robust informed embedding with low complexity for digital watermarking,'' International Journal of Innovative Com-
puting, Information and Control (IJICIC), vol. 8, no. 9, Sep. 2012.
[27] J.-J.Wang, H. Chen and H. Liang, ``A Trellis-Based Informed Embedding With Linear Codes for Digital Watermarking,'' in Proc. IEEE ISCE 2011, Singapore,
June, 2011.
[28] M. F. Horng, B. C. Huang, M. H. Lee and Y. H. Kuo, ``A DC-based approach to robust watermarking with Hamming-code,'' International Journal of Innovative Computing, Information and Control (IJICIC), vol. 5, no. 7, pp. 1911-1917, Jul. 2009.
[29] Zhaoxia Yin, Chinchen Chang and Yanping Zhang, ``An information hiding scheme based on (7,4) Hamming code oriented wet paper codes,'' International Journal of Innovative Computing, Information and Control (IJICIC), vol. 6, no. 7, pp. 3121-3130, Jul. 2010.
[30] L. D. Li and B. L. Guo, ``Robust image watermarking using feature based local invariant regions,'' International Journal of Innovative Computing, Information
and Control (IJICIC), vol. 4, no. 8, pp. 1977-1986, Aug. 2008.
[31] J. A. Bloom, I. J. Cox, T. Kalker, J.-P. M. G. Linnartz, M. L. Miller, and C. B. S. Traw, ``Copy protection for digital video," Proc. IEEE Special Issue
on Identi¯cation and Protection of Multimedia Information, vol. 87, no. 7, pp. 1267-1276, Jul. 1999.
[32] Li Fan, Tiegang Gao and Qunting Yang, ``A novel watermarking scheme for copyright protection based on adaptive joint image feature and visual secret
sharing,'' International Journal of Innovative Computing, Information and Control (IJICIC), vol. 7, no. 7(A), pp. 3679{3694, Jul. 2011.
[33] D. Boneh and J. Shaw, ``Collusion-secure ngerprinting for digital data,'' IEEE Trans. Inf. Theory, vol. 44, no. 5, pp. 1897-1905, 1998.
[34] D. H. Im, Y. Hu, H. Y. Lee and H. K. Lee, ``Watermarking curves for ¯ngerprinting digital maps,'' International Journal of Innovative Computing, Information
and Control (IJICIC), vol. 6, no. 3(B), pp. 1257-1269, Mar. 2010.
[35] D. Kundeur and D. Hatzinakos, ``Digital watermarking for telltale tamperprooing and authentication,'' Proc. IEEE, vol. 87, no. 7, pp. 1167-1180, Jul. 1999.
[36] Ayhan lmaz, A. Ayd Alatan, ``Error detection and concealment for video transmission using information hiding,'' Signal Processing: Image Communication, vol. 23, Issue 4, pp. 298-312, Apr. 2008.
[37] S. D. Lin and Y. H. Huang, ``An integrated watermarking technique with tamper detection and recovery,'' International Journal of Innovative Computing,
Information and Control (IJICIC), vol. 5, no. 11(B), pp. 4309-4316, Nov. 2009.
[38] J. T. Wang, Y. W. Yang, Y. T. Chang and S. S. Yu, ``A high verification capacity reversible fragile watermarking scheme for 3D models,'' International Journal of Innovative Computing, Information and Control (IJICIC), vol. 7, no. 1, pp. 365-378, Jan. 2011.
[39] F. Bartolini, A. Tefas, M. Barni, and I. Pitas, ``Image authentication techniques for surveillance applications,'' Proc. IEEE, vol. 89, no. 10, pp. 1403-1418, Oct. 2001.
[40] E. Martinian and G. W. Wornell, ``Authentication with distortion constraints,'' in Proc. IEEE Int. Conf. Image Processing, pp. 17-20, 2002.
[41] I. J. Cox, M. L. Miller, and J. A. Bloom, Digital Watermarking, New York: Morgan Kaufmann, 2001.
[42] P. Moulin and R. Koetter, ``Data-hiding codes,'' Proc. IEEE, vol. 93, no. 12, pp. 2083-2126, Dec. 2005.
[43] I. J. Cox, M. L. Miller, and A. McKellips, ``Watermarking as communications with side information,'' Proc. IEEE, vol. 87, pp. 1127-1141, Jul. 1999.
[44] M. H. M. Costa, ``Writing on dirty paper,'' IEEE Trans. Inf. Theory, vol. 29, pp. 439-441, 1993.
[45] Y. Sun, Y. Yang, A. D. Liveris, V. Stankovic, and Z. Xiong, ``Near-capacity dirty-paper code design: a source-channel coding approach," IEEE Trans. Inf. Theory, vol. 55, no. 7, pp. 3013-3031, Jul. 2009.
[46] R. Barron, B. Chen, and G. W. Wornell, ``The duality between information embedding and source coding with side information and some applicaitons,'' IEEE Trans. Inf. Theory, vol. 49, no. 5, pp. 1159-1180, May 2003.
[47] S. S. Pradhan, J. Chou, and K. Ramchandran, ``Duality bewteen source coding and channel coding and its extension to the side information case,'' IEEE Trans. Inf. Theory, vol. 49, no. 5, pp. 1181-1203, May 2003.
[48] Chun-Shien Lu, ``Towards robust image watermarking: combining content dependent key, moment normalization, and side-informed embedding,'' Signal Processing: Image Communication, vol. 20, Issue 2, pp. 129-150, Feb. 2005.
[49] R. Zamir, S. Shamai, and U. Erez, ``Nested linear/lattice codes for structured multierminal binning," IEEE Trans. Inf. Theory, vol. 48, no. 6, pp. 1250-1276,
Jun. 2002.
[50] M. J.Wainwright, ``Sparse graph codes for side information and binning,'' IEEE Signal Processing Mag., vol. 24, no. 5, pp. 47-57, Sep. 2007.
[51] Claude Desset, Benot Macq, Luc Vandendorpe, ``Block error-correcting codes for systems with a very high BER: Theoretical analysis and application to the protection of watermarks,'' Signal Processing: Image Communication, vol. 17, Issue 5, pp. 409-421, May. 2002.
[52] M. L. Miller, I. J. Cox, and J. A. Bloom, ``Informed embedding: exploiting image and detector information during watermark insertion,'' in IEEE Int. Conf. on Image Processing, Sep. 2000.
[53] M. L. Miller, G. J. Doerr, and I. J. Cox, ``Applying informed coding and embedding to design a robust high-capacity watermark,'' IEEE Trans. Image Process., vol. 13, no. 6, pp. 792-807, Jun. 2004.
[54] L. Lin, G. Doerr, I. Cox, and M. Miller, ``An e±cient algorithm for informed embedding of dirty-paper trellis codes for watermarking,'' in Proc. IEEE Int. Conf. Image Processing, Italy, 2005.
[55] G. D. Forney, ``The Viterbi algorithm,'' Proc. IEEE, vol. 61, pp. 268-278, Mar. 1973.