Abstract
As digitalized content rapidly proliferates in networked systems, content security necessarily arises as one of the most important issues. Many developers have studied techniques for allowing only authorized persons to access content. Recently, video scrambling techniques, one type of the authorizing tools, have been introduced. However, they change the original video data, which often increases the bit rate of the source data. To overcome this problem, we propose a scrambling technique which deliberately distorts the original video sequences in a reversible way by arbitrarily relocating the differential motion vectors and MB (macroblock) starting positions in a slice. This method can be applied to most common video coding techniques such as MPEG-1/2/4, and H.264.
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References
Macq, B., Quisquate, J.: Digital images multiresolution encryption. Interactive Multimedia Assoc. Intell. Property Proj., 179–186 (January 1994)
Katta, N., et al.: Scrambling apparatus and descramble apparatus. U.S. patent 5377266 (December 27, 1994)
Jang, J.: Digital video scrambling method, Korean patent 0151199 (June 18, 1998)
Zeng, W., Lei, S.: Efficient frequency domain video scrambling for content access control. In: ACM Multimedia 1999 (November 1999)
Zeng, W., Lei, S.: Efficient frequency domain selective scrambling of digital video. IEEE Transactions on Multimedia, 118–129 (2003)
Ahn, J., Shim, H., Jeon, B., Choi, I.: Digital Video Scrambling Method Using Intra Prediction Mode. In: Aizawa, K., Nakamura, Y., Satoh, S. (eds.) PCM 2004. LNCS, vol. 3333, pp. 386–393. Springer, Heidelberg (2004)
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© 2005 Springer-Verlag Berlin Heidelberg
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Kwon, S.G., Choi, W.I., Jeon, B. (2005). Digital Video Scrambling Using Motion Vector and Slice Relocation. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2005. Lecture Notes in Computer Science, vol 3656. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11559573_26
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DOI: https://doi.org/10.1007/11559573_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29069-8
Online ISBN: 978-3-540-31938-2
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