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標題: 使用迴旋碼作二元資料藏匿之研究
Binary Data Hiding Schemes Using Convolutional Codes
作者: 戴文嬋
Tai, Wen-Chan
關鍵字: 隱匿學;Steganography;資料藏匿;迴旋碼;負載;截斷;Data hiding;Convolutional code;Payload;Puncture
出版社: 電機工程學系所
引用: [1] S. Lin and D.J. Costello , Error Control Coding Fundamentals and Applications. Englewood Cliffs, NJ: Prentice-Hall, 1983. [2] Proakis, J. G. Digital Communications, 3rd ed., McGraw- Hill, New York, 1995. [3] T. Filler, J. Judas and J. Fridrich, “Minimizing additive distortion in steganography using syndrome-trellis codes ,” IEEE Trans. In- formation Forensics and Security, vol. 6, pp. 1, 2011. [4] J. Fridrich and D. Soukal, “Matrix embedding for large payloads,”IEEE Trans. Information Forensics and Security, vol. 1, pp. 390–395, 2006. [5] R. Crandall. Some notes on steganography. Steganography Mailing List, available from http://os.inf.tu-, 1998. [6] M. J. Wainwright, “Sparse Graph Codes for Side Information and Binning,” IEEE Signal Process. Mag., vol. 24, no. 5, pp. 47–57, Sep.2007. [7] J. Bierbrauer, On Crandall’s Problem [Online]. Available: 1998. [8] 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. [9] F. Galand and G. Kabatiansky. Information hiding by coverings. In Proceedings ITW2003, Paris, France, 2003, pages 151–154. [10] J. Fridrich and D. Soukal, “Matrix embedding for large payloads,”IEEE Trans. Inform. Forens. Sec., vol. 1, no. 3, pp. 390–395, Sep.2006. [11] 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. [12] Yunkai Gao, Xiaolong Li and Bin Yang, “Employing optimal matrix for efficient matrix embedding,” in Proc. IIH-MSP2009, pp.161–165, Sep. 2009.
本篇論文是利用迴旋碼應用於二元資料藏匿,針對藏匿容量可分為小負載及大負載迴旋碼藏匿,其主要原理利用線性徵狀碼當成一組合選擇的集合,而在此集合中找尋一組最接近載體的向量碼。而建造一高維度 k的迴旋碼是非常困難的,故小負載迴旋碼藏匿中,截斷技術降低複雜度及調整碼率優點被應用於此篇論文,也列出迴旋碼編碼之最佳截斷矩陣,我們將探討迴旋碼之藏匿容量、失真度與嵌入效率之關係,其相關方法與結果將在本文中呈現。

A data hiding algorithm for binary data based on convolutional code is proposed. Embedding capacity can be divided into small Payload and large Payload hiding. The main purpose of the thesis regarding the linear syndrome code as the select combination of collection that we can find the vector closest to the host.In general, constructing a high dimension ''k'' is very diffcult. In the small payload of convolutional code for data hiding, puncturing is applied for reducing the complexity and adjusting the code rate. Furthermore, we also lists the best puncturing table by experiments. We will discuss capacity, distortion and embedding efficiency in the thesis. Methods and results will be demostrated in this thesis.
其他識別: U0005-1707201216351600
Appears in Collections:電機工程學系所

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