臺灣博碩士論文加值系統

在現行的資訊隱藏方法中，LSB取代法為最常見的資訊隱藏法。透過修改對影像最無影響的最低有效位元，讓人類眼睛無法識別的情況下將秘密資訊藏入影音載體中，讓資訊更安全的在網路中傳輸。而影像中並非所有區塊都有能力承載相同長度的秘密訊息，因此可透過尋找影像紋理的方式找出影像紋理特徵，並在影像複雜區藏入更多的秘密資訊以達到高藏量的效果。本研究透過結合了邊緣偵測法更有效的找出影像紋理，針對擁有不同影像紋理特徵的區塊分別以不同的演算法進行秘密資訊藏入。本研究藉由像素差值法有效的提高平滑區的資訊藏量；複雜的邊緣區域則使用LSB取代法或是結合LSB取代法的商數差值法有效提升複雜區的藏量。且本研究所提出的方法能有效抵抗RS偵測法的攻擊，有效的提高了秘密影像的安全性。

In the current steganography method, the least significant bits (LSBs) substitution is the most common. By modifying the least significant bits, the secret messages can be hidden in the media carrier and cannot be perceived by the human visual system, making information transmission via the Internet more secure. Not all blocks in the image have the ability to carry secret messages of the same length and high confidence. In this paper, the image texture can effectively be found by the edge detection method, and the secret messages is embedded by different algorithms for the edge area and non-edge area. The pixel value differencing (PVD) is used to effectively improve the information of the smooth region. The complex edge region uses the LSB substitution or the quotient value difference (QVD) combination with the LSB substitution to effectively increase the embedding capacity. Moreover, the method proposed in this paper can effectively resist RS attacks and improve the security of secret images.

目錄
摘要 i
Abstract ii
目錄 iii
圖目錄 v
表目錄 vii
1. 緒論 1
1.1. 研究背景 1
1.2. 研究動機與目的 2
1.3. 研究架構 3
2. 文獻探討 5
2.1. 文獻相關符號與定義 5
2.2. 邊緣偵測法 5
2.2.1. Sobel算子(Sobel Operator)[18] 5
2.2.2. Canny運算子(Canny Operator) [19] 7
2.3. 最低有效位元取代法(Least Significant Bits Substitution)[9] 7
2.4. 以邊緣偵測為基礎的資訊隱藏法[13] [14] [15] 8
2.5. 以差值法為基礎的資訊隱藏法 8
2.5.1. 像素差值法(Pixel Value Differencing, PVD) [10] 9
2.5.2. 商數差值法與最低有效位元取代法(QVD and LSBs Substitution)[17] 10
3. 本研究方法 12
3.1. 符號定義 12
3.2. 以邊緣偵測為基礎的LSB取代法及像素差值法 12
3.2.1. 邊緣偵測前的影像預處理 13
3.2.2. 以邊緣偵測為基礎的LSB取代法及像素差值法藏入流程 15
3.2.3. 問題像素對的發生條件及其解決方法 17
3.2.4. 以邊緣偵測為基礎的LSB取代法及像素差值法取出流程 18
3.2.5. 以邊緣偵測為基礎的LSB取代法及像素差值法範例說明 19
3.3. 改善以邊緣偵測為基礎的LSB取代法及像素差值法 21
3.3.1. 改善以邊緣偵測為基礎的LSB取代法及像素差值法藏入流程 22
3.3.2. 改善以邊緣偵測為基礎的LSB取代法及像素差值法取出流程 23
3.3.3. 改善以邊緣偵測為基礎的LSB取代法及像素差值法範例演示 24
3.4. 以邊緣偵測為基礎的商數差值法及像素差值法 26
3.4.1. 以邊緣偵測為基礎的商數差值法及像素差值法藏入流程 26
3.4.2. 以邊緣偵測為基礎的商數差值法及像素差值法取出流程 28
3.4.3. 以邊緣偵測為基礎的商數差值法及像素差值法範例說明 29
3.5. 改善以邊緣偵測為基礎的商數差值法及像素差值法 31
3.5.1. 改善以邊緣偵測為基礎的商數差值法及像素差值法藏入流程 31
3.5.2. 改善以邊緣偵測為基礎的商數差值法及像素差值法取出流程 33
3.5.3. 改善以邊緣偵測為基礎的商數差值法及像素差值法範例演示 35
4. 實驗結果 37
4.1. 實驗環境及實驗用圖 37
4.2. 不同邊緣偵測法所產生的邊緣數量及邊緣像素對數量 38
4.3. 不同影像在本研究方法中的表現 38
4.4. 各方法下之標準圖實驗結果比較 46
4.5. 本研究方法之RS攻擊分析 48
5. 結論與未來展望 51
5.1. 結論 51
5.2. 未來展望 51
參考文獻 52

[1] R. Davis, “The data encryption standard in perspective,” IEEE Communications Society Magazine, vol. 16, no. 6, pp 5-9, 1978.
[2] J. Nechvatal, E. Barker, L. Bassham, W. Burr, M. Dworkin, J. Foti, and E. Roback, “Report on the Development of the Advanced Encryption Standard (AES),” Journal of Research of NIST, vol. 106, no. 3, pp 511-577, 2001.
[3] C. Mclvor ; M. McLoone ; J.V. McCanny, “Fast Montgomery modular multiplication and RSA cryptographic processor architectures,” The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, pp 379-384, 2003
[4] N. Provos and P. Honeyman, “Hide and Seek: An Introduction To Steganography,” IEEE Security & Privacy, vol. 1, no. 3, pp 32-44, 2003.
[5] K. Bennett, “Linguistic Steganography: Survey, Analysis, and Robustness Concerns for Hiding Information in Text,” Purdue University, CERIAS Tech. Report 2004-13, 2004.
[6] X.P. Zhang and S.Z. Wang, “Steganography using multiple-base notational system and human vision sensitivity,” IEEE Signal Processing Letters, vol. 12, no. 1, 2005.
[7] X. Li, J. Li, B. Li, and B. Yang, “High-fidelity reversible data hiding scheme based on pixel-value-ordering and prediction-error expansion,” Signal processing, vol. 93, no. 1, pp. 198-205, 2013.
[8] J. Tian, “Reversible data embedding using a difference expansion,” IEEE transactions on circuits and systems for video technology, vol. 13, no. 8, pp. 890-896, 2003.
[9] C.K. Chan, L.M. Cheng “Hiding data in images by simple LSB substitution,” Pattern Recognition, vol. 37, no. 3, pp 469-474, 2004.
[10] D.C. Wu, W.H. Tsai, “A steganographic method for images by pixel-value differencing,” Pattern Recognition Letters , vol. 24, pp 1613-1626, 2003.
[11] X.P. Zhang and S.Z. Wang, “Efficient Steganographic Embedding by Exploiting Modification Direction,” IEEE Communications Letters, vol. 10, no. 11, pp 781-783, 2006.
[12] W.J. Chen, C.C. Chang, T. H. N. Le ,“High payload steganography mechanism using hybrid edge detector,” Expert Systems with Applications, vol. 37, no. 4, pp 3292–3301, 2010
[13] C.F. Lee, C.C. Chang, and P.L. Tsou, “Data hiding scheme with high embedding capacity and good visual quality based on edge detection,” 2010 The Fourth International Conference on Genetic and Evolutionary Computing, pp.654–657, 2010.
[14] H. Dadgostar, F. Afsari, “Image steganography based on interval-valued intuitionistic fuzzy edge detection and modified LSB,” Journal of Information Security and Applications, vol. 30, pp 94-104, 2016.
[15] J.-L. Bai, C.-C. Chang, T.-S. Nguyen, C. Zhu, Y.-J. Liu, “A high payload steganographic al-gorithm based on edge detection,” Displays, vol. 46, pp 42-51, 2017.
[16] H.C. Wu; N.I. Wu; C.S. Tsai; M.S. Hwang, “Image steganographic scheme based on pixel-value differencing and LSB replacement methods,” IEE Proceedings - Vision, Image, and Signal Processing, vol. 152, no. 5, pp 611-615, 2005.
[17] K.H. Jung, “Data hiding scheme improving embedding capacity using mixed PVD and LSB on bit plane,” Journal of Real-Time Image Processing, vol. 14, no. 1, pp 127-136, 2018.
[18] N. Kanopoulos ; N. Vasanthavada ; R.L. Baker, “Design of an image edge detection filter using the Sobel operator,” IEEE Journal of Solid-State Circuits, vol. 23, no. 2, 1988.
[19] J. Canny, “A Computational Approach to Edge Detection,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. PAMI-8, no. 6, 1986.