博碩士論文 90521075 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:20 、訪客IP:54.91.41.87
姓名 孫士韋(Shih-Wei Sun)  查詢紙本館藏   畢業系所 電機工程學系
論文名稱 多媒體安全:加密,浮水印,及播送技術與應用
(Multimedia Security: Encryption, Watermarking, and Distribution Technologies and Applications)
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摘要(中) 隨著無線通訊與網路技術的進步,多媒體資料在網路上的傳輸機會與日俱增。由於多媒體資料的豐富性和多樣性,以及無線網路普及率節節升高,多媒體資料在不同使用者之間的分享與交換行為日益普遍。然而,多媒體資料在傳輸的過程中,若沒有加以保護,也就是所謂的多媒體安全技術若沒有適當發展,多媒體資料的內容將被任意存取與分享,而侵犯多媒體擁有者的著作權。在本論文中,多媒體安全的各種技術與應用,將被廣泛的討論,尤其是多媒體加密,多媒體浮水印,以及多媒體播送技術與應用。論文中我們將提及多媒體安全中目前極具挑戰性的問題,並且針對這些問題提出我們的看法與解決方案。
在本論文中,我們將從多媒體安全的第一道防線-多媒體加密,開始討論起。因為加密過後的多媒體資料在傳輸的過程當中可能遇到具有錯誤特性的網路環境,我們提出了一套以媒體赫序(Media Hash)為基礎的視訊錯誤回復機制。接著,我們會著墨於多媒體安全的第二道防線,多媒體浮水印。我們提出了一套強健性的多媒體浮水印技術,能夠抵抗幾何攻擊以及浮水印預估攻擊。此外,我們還提出了一套抵抗時間軸非同步攻擊的視訊浮水印同步技術,用來增加多媒體浮水印技術的強韌性。當多媒體安全的兩道防線都建立了,一個合適的多媒體散佈架構是相當需要的。在本論文中,我們提出了與AACS(advanced access control system)相容的結合式加密與多媒體指紋嵌入架構技術。與該架構相關的安全議題,挑戰,與相對應的解決方案也在此一並討論。
多媒體加密技術在安全的存取多媒體資料技術中扮演了第一道防線。傳統的加密技術能夠提供安全性的保障,但是連任何一個位元錯誤都無法容忍,這在多媒體傳輸應用中並不實用。為了達到強健性的多媒體加密技術,在多媒體傳輸中必須能夠具備錯誤回復能力。本論文中提出了一套利用嵌入於殘餘資料之以多媒體赫序為基礎的結合式視訊加密及傳輸機制,期望達到對於遺失視訊封包的移動向量預測及補償,同時能夠保持格式相容和密碼學上的安全性。有趣的是,既然視訊區塊赫序能夠保存精華的視訊內容,利用搜尋類似的區塊,移動向量預測隱含了強健性媒體赫序比對精神,這就是本方法的獨特性。
多媒體保護的第二道防線是浮水印技術。現存浮水印技術最主要的缺點是對於廣泛的幾何攻擊抵抗能力。此外,我們發現現存文獻若能夠抵抗預估浮水印攻擊,便降低了抵抗幾何攻擊的能力。基於以上的看法,在本論文中,我們提出了同時能夠抵抗幾何攻擊及浮水印預估攻擊的技術。本技術主要包含三個部份:(1)強健的碎塊產生和以碎塊為基礎的浮水印技術以抵抗幾何攻擊,(2)建立以媒體赫序和內容為基礎的浮水印以抵抗浮水印預估性攻擊,(3)提出一套以錯誤機率為導向的浮水印偵測技術,用來決策浮水印是否存在,以達到錯誤正向及錯誤負向判斷的取捨。
此外,同步問題在視訊浮水印技術中是一個具有挑戰性的問題。我們提出了一套基以訊框輪廓統計特性為基礎的時軸同步技術。訊框輪廓在x和y方向上以平均值和變異數代表一個訊框的特性,如此得到的統計值可以當作一個訊框的特徵。一連串的視訊訊框可以在解碼端進行訊框特徵比對,以達到再同步效應。在接收端,諸如:訊框置換,遺失,和插入等時軸非同步攻擊,藉由本技術提出的訊框統計特比對,可以達到再同步效應,以利於最後的浮水印偵測。
一旦多媒體安全的第一和第二道防線都經過適當的設計,一個安全的多媒體播送架構是必要的。本論文中提出了一套結合式加密和多媒體指紋嵌入的方法,並且可以和AACS(advanced access control system)相容。由於目前AACS是對多媒體存取控制的領導技術,並且是多家多媒體播送公司所共同制定的標準,因此我們發展的技術期望與這樣的標準在概念上相容。在本技術中,我們探討了許多可能的攻擊點以及抵抗措施,此外,我們提出了多重攻擊點所產生的串謀攻擊以及合適的抵抗對策。在本論文中,(1)我們提出了在不同點之間的多媒體加密技術,(2)我們提出了可複寫式的多媒體指紋嵌入技術,用以抵抗多重攻擊點所產生的串謀攻擊,(3)我們設計了SPSM(Spectral Perceptual Security Metric)來評估多重加密所能夠達到的安全程度。
摘要(英) With the development progress of wireless communications and networking technologies, the transmission opportunities of multimedia data become increasing. Because of the planarity and diversity of multimedia, and the increasing rate of wireless network popularity, the sharing and exchanging actions among different users are common. However, during the transmission process, if the multimedia data is not properly protected, i.e. if the multimedia security technologies are not properly developed, multimedia content would be accessed and shared without any limitation, forcing the copyright of the multimedia content owner. In this dissertation, the multimedia applications and technologies would be widely discussed, especially multimedia encryption, watermarking, and distribution applications and technologies. In this dissertation, the recent most challenging problems in multimedia security would be addressed, discussed, and properly dealt with.
In this dissertation, the multimedia security issue is discussed from the first defense line: multimedia encryption. Because the protected encrypted multimedia data would be distributed over the error-prone network environment, a media-hash based video error resilient technique is proposed. Next, the second defense line, multimedia watermarking, is addressed. A robust image watermarking technique against geometric distortions and watermark estimation attack (WEA) is proposed. In addition, a temporal re-synchronization technique for video watermarking is discussed to improve the robustness. While the two defense lines for multimedia security are well-developed, a proper secure multimedia distribution framework is necessary. An advanced access control system (AACS)-compatible joint encryption and fingerprinting technique is proposed to form a proper framework. Some security issues, challenges, and solutions are addressed.
Media encryption technologies actively play the first line of defense in securing the access of multimedia data. Traditional cryptographic encryption can achieve provable security but is unfortunately sensitive to a single bit error, which will cause an unreliable packet to be dropped creating packet loss. In order to achieve robust media encryption, the requirement of error resilience can be achieved with error-resilient media transmission. This dissertation proposes a video joint encryption and transmission (video JET) scheme by exploiting media hash-embedded residual data to achieve motion estimation and compensation for recovering lost packets, while maintaining format compliance and cryptographic provable security. Interestingly, since video block hash preserves the condensed content to facilitate search of similar blocks, motion estimation is implicitly performed through robust media hash matching -- which is the unique characteristic of our method.
The second defense line of multimedia protection is watermarking. The major disadvantage of existing watermarking methods is their limited resistance to extensive geometric attacks. In addition, we have found that the weakness of multiple watermark embedding methods that were initially designed to resist geometric attacks is their inability to withstand the watermark-estimation attacks (WEAs), leading to reduce resistance to geometric attacks. In view of these facts, this dissertation proposes a robust image watermarking scheme that can withstand geometric distortions and WEAs simultaneously. Our scheme is mainly composed of three components: (i) robust mesh generation and mesh-based watermarking to resist geometric distortions; (ii) construction of media hash-based content-dependent watermark (CDW) to resist WEAs; and (iii) a mechanism of false positive-oriented watermark detection, which can be used to determine the existence of a watermark so as to achieve a trade-off between correct detection and false detection.
In addition, synchronization for video watermarking is a challenging problem. We propose a novel temporal synchronization method for video watermarking by matching the profile statistics. The profile statistics, represented by the characteristic parameters such as position mean and variance in x- and y-directions, of a frame in a video sequence can easily be calculated and sent as the side information to the receiver. At the receiving end, temporal attacks such as transposition, dropping, and insertion can be detected by comparing the side information and the characteristic parameters calculated from the received video.
While the two defense lines for multimedia security are well-developed, a proper secure multimedia distribution framework is necessary. In this dissertation, a new multimedia joint encryption and fingerprinting (JEF) scheme embedded into the advanced access control system (AACS) is proposed. AACS is selected because it has been the leading technology in access control developed by many significant companies for multimedia distribution. In this AACS-compatible JEF system, many attack points exist and can be explored to defend it. Furthermore, multiple attack points can form multi-point collusion attacks, which also engage the proposed system. In this paper, (i) we propose multimedia encryption at different points to resist some attacks points; (ii) we propose rewritable fingerprint embedding (RFE) to deal with some multi-point collusion attacks; (iii) we design SPSM to evaluate the degree of security which multiple encryptions are applied.
關鍵字(中) ★ 浮水印
★ 加密
★ 多媒體安全
★ 播送
關鍵字(英) ★ Watermarking
★ Multimedia Security
★ Distribution
★ Encryption
論文目次 1 Introduction 1
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 The Organization of the Dissertation . . . . . . . . . . . . . . . . . . . . 3
2 Multimedia Encryption and Error Protection 5
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.1.2 Related Work about Error-Resilient Video Encryption . . . . . . 8
2.1.3 Related Work about Error-Resilient Video Transmission . . . . . 8
2.1.3.1 Encoder-level . . . . . . . . . . . . . . . . . . . . . . 9
2.1.3.2 Transport-level . . . . . . . . . . . . . . . . . . . . . . 9
2.1.3.3 Decoder-level . . . . . . . . . . . . . . . . . . . . . . 9
2.1.3.4 Data Hiding-based . . . . . . . . . . . . . . . . . . . . 9
2.1.3.5 Side Information-based . . . . . . . . . . . . . . . . . 10
2.1.4 Our Observations . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.2 Problem Statement: Error-Resilient Video Joint Encryption and Transmission
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.3 Media Hash . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.3.1 General Principle . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.3.2 Proposed Video Block Hashing . . . . . . . . . . . . . . . . . . 15
2.4 Proposed Error-Resilient Video Joint Encryption and Transmission Method 19
2.4.1 Basic Structure of H.264 and Light-Weight Encryption . . . . . . 21
2.4.2 Media Hash Hiding at Encoder for Error Resilience . . . . . . . . 22
2.4.2.1 Analysis of Distortions Caused by Hash Embedding . . 23
2.4.3 Media Hash Extraction at Decoder . . . . . . . . . . . . . . . . . 24
2.4.4 Two-Stage Hash Matching at Decoder . . . . . . . . . . . . . . . 24
2.5 Analysis of Error Recovery between Our Method and Forward Error Correction
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.5.1 Error Resilience of Video JET . . . . . . . . . . . . . . . . . . . 29
2.5.2 Error Resilience of FEC . . . . . . . . . . . . . . . . . . . . . . 29
2.5.3 Video JET vs. FEC . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.6 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
2.6.1 Experimental Setup . . . . . . . . . . . . . . . . . . . . . . . . . 32
2.6.2 Error Resilience of The Proposed Method . . . . . . . . . . . . . 33
2.6.3 Verification of Analytic Results . . . . . . . . . . . . . . . . . . 36
2.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
3 MultimediaWatermarking: ImageWatermarking 45
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
3.2 Robust Feature Extraction and Media Hash-based Content-DependentWatermark
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
3.2.1 Robust Feature Extraction . . . . . . . . . . . . . . . . . . . . . 52
3.2.1.1 Gaussian Kernel Filtering . . . . . . . . . . . . . . . . 52
3.2.1.2 Local Maximum Determination . . . . . . . . . . . . . 53
3.2.1.3 How Can We Choose s ? . . . . . . . . . . . . . . . . 54
3.2.2 Content-Dependent Watermark . . . . . . . . . . . . . . . . . . 55
3.3 Proposed Watermarking Method . . . . . . . . . . . . . . . . . . . . . . 57
3.3.1 Watermark Embedding . . . . . . . . . . . . . . . . . . . . . . . 57
3.3.1.1 Mesh Generation . . . . . . . . . . . . . . . . . . . . 57
3.3.1.2 Content-Dependent Watermark Generation . . . . . . . 58
Mesh Normalization . . . . . . . . . . . . . . . . . . . . 59
Mesh-based Hash Extraction . . . . . . . . . . . . . . . . 59
Media Hash-based Content-dependent Watermark . . . . . 59
3.3.1.3 Arrangement of Watermark Bits for Embedding . . . . 60
3.3.1.4 Mesh-based Embedding . . . . . . . . . . . . . . . . . 60
3.3.2 Watermark Extraction . . . . . . . . . . . . . . . . . . . . . . . 62
3.3.2.1 Scale Matching Process . . . . . . . . . . . . . . . . . 62
3.3.2.2 Media Hash-based Content-Dependent Watermark Extraction
. . . . . . . . . . . . . . . . . . . . . . . . . . 64
3.3.3 Complexity of Our Method . . . . . . . . . . . . . . . . . . . . . 65
3.4 False Positive-Oriented Determination of the Existence of a Watermark . 67
3.4.1 Comparison with Other Methods . . . . . . . . . . . . . . . . . . 70
3.5 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
3.5.1 Resistance to Non-geometric Attacks . . . . . . . . . . . . . . . 73
3.5.2 Resistance to Geometric Attacks . . . . . . . . . . . . . . . . . . 74
3.5.3 Comparisons with Bas et al.’s Scheme [8] . . . . . . . . . . . . . 74
3.5.4 Resistance to Watermark-Estimation Attacks (WEAs) . . . . . . 75
3.5.5 Discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
3.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
4 MultimediaWatermarking: VideoWatermarking Synchronization 90
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
4.2 Profile Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
4.2.1 Profile of An Image . . . . . . . . . . . . . . . . . . . . . . . . . 92
4.2.2 Moments of The Profiles . . . . . . . . . . . . . . . . . . . . . . 93
4.3 System Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
4.4 Temporal Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
4.5 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
4.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
5 Secure Multimedia Distribution 100
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
5.1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
5.1.2 RelatedWork about Joint Multimedia Encryption and Fingerprinting
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
5.1.3 Advanced Access Content System . . . . . . . . . . . . . . . . . 104
5.1.4 Our Contributions . . . . . . . . . . . . . . . . . . . . . . . . . 105
5.2 The Structure of Proposed Joint Multimedia Encryption and Fingerprinting
(JEF) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
5.3 Possible Attack Points and Multi-point Collusion Attacks . . . . . . . . . 109
5.3.1 Possible Attack Points . . . . . . . . . . . . . . . . . . . . . . . 110
5.3.2 Multi-point Collusion Attacks . . . . . . . . . . . . . . . . . . . 111
5.4 Rewritable Fingerprint Embedding . . . . . . . . . . . . . . . . . . . . . 113
5.5 Spectrum Perceptual Security Metrics . . . . . . . . . . . . . . . . . . . 116
5.6 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
5.6.1 Encryption Results . . . . . . . . . . . . . . . . . . . . . . . . . 118
5.6.2 Simulations for The Derived Lower Bound a0 for RFE . . . . . . 119
5.6.2.1 State Change (+1;!1) . . . . . . . . . . . . . . . . . 119
5.6.2.2 State Change (!1;+1) . . . . . . . . . . . . . . . . . 120
5.6.2.3 State Change (!1;!1) . . . . . . . . . . . . . . . . . 120
5.6.2.4 State Change (+1;+1) . . . . . . . . . . . . . . . . . 120
5.6.2.5 Transparency and False Alarm tests . . . . . . . . . . . 121
5.6.3 SPSM Measurement . . . . . . . . . . . . . . . . . . . . . . . . 122
5.6.4 Single Collusion Attack at Point H . . . . . . . . . . . . . . . . . 123
5.6.5 Multi-point Collusion Attack . . . . . . . . . . . . . . . . . . . . 123
5.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
6 Conclusions 132
Bibliography 134
參考文獻 [1] http://www.aacsla.com/specifications/specs091/AACS Spec Prerecorded 0.91.pdf .
[2] http://iphome.hhi.de/suehring/tml/download/old jm/jm96.zip.
[3] http://www.ece.cmu.edu/?ece796/mpeg4.pdf
[4] A. Aaron, S. Rane, and B. Girod, “Wyner-Ziv Video Coding with Hash-based Motion
Compensation at the Receiver,” Proc. IEEE Int. Conf. on Image Processing,
Vol. 5, pp. 3097-3100, 2004.
[5] A. J. Ahumada and H. A. Peterson, “Luminance-model-based DCT Quantization
for Color Image Compression,” Proceedings of the SPIE, 1666: pp. 365-374, 1992.
[6] M. Alghoniemy and A. H. Tewfik, “Geometric Invariance in ImageWatermarking,”
IEEE Trans. on Image Processing, Vol. 13, No. 2, pp. 145-153, 2004.
[7] E. Ayanoglu, R. Pancha, A. R. Reibman, and S. Talwar, “Forward Error Control
for MPEG-2 Video Transport in a Wireless ATM LAN,” ACM/Baltzer Mobile Networks
and Applications, Vol. 1, No. 3, pp. 245-258, 1996.
[8] P. Bas, J. M. Chassery, and B. Macq, “Geometrically InvariantWatermarking Using
Feature Points,” IEEE Trans. Image Processing, Vol. 11, No. 9, pp.1014-1028,
2002.
[9] J. Bloom, “Security and Rights Management in Digital Cinema,” Proc. IEEE Intl.
Conf. Acoustics, Speech and Signal Processing, Vol. 4, pp. 712-715, 2003.
[10] D. Boneh and J. Shaw, “Collusion-secure Fingerprinting for Digital Data,” IEEE
Trans. Inform. Theory, Vol. 44, pp. 1897-1905, 1998.
[11] M. Chen, Y. He, and R. L. Landgelijk, “A Fragile Watermark Error Detection
Scheme for Wireless Video Communications,” IEEE Trans. on Multimedia, Vol.
7, No. 2, pp. 201-211, 2005.
[12] I. J. Cox, J. Kilian, F. T. Leighton, and T. Shamoon, “Secure Spread Spectrum
Watermarking for Multimedia,” IEEE Trans. Image Processing, Vol. 6, No. 12, pp.
1673-1687, 1997.
[13] I. J. Cox and M. L. Miller, “Electronic Watermarking: The First 50 Years,” Proc.
IEEE Fourth Workshop on Multimedia Signal Processing, pp. 225 -230, 2001.
[14] I. J. Cox, M. L. Miller, and J. A. Bloom, “Digital Watermarking,” Morgan Kaufmann
Publishers, 1/e, USA, 2002.
[15] S. Craver, N. Memon, BL Yeo, and M. M. Yeung, “Resolving Rightful Ownerships
with Invisible Watermarking Techniques: Limitations, Attacks, and Implications,”
IEEE Journal on Selected Areas in Communications, Vol. 16, No. 4, pp. 573-586,
1998.
[16] R. Dursternfeld, “Algorithm 235: Random Permutation [G6],” Communications of
the ACM, pp. 420, 1964.
[17] J. Fridrich, “Visual Hash for Oblivious Watermarking,” Proc. SPIE: Security and
Watermarking of Multimedia Contents II, Vol. 3971, pp. 286-294, 2000.
[18] “Draft ITU-T recommendation and final draft international standard of joint video
specification (ITU-T Rec. H.264/ISO/IEC 14 496-10 AVC,” Joint Video Team
(JVT) of ISO/IEC MPEG and ITU-T VCEG, JVTG050, 2003.
[19] C. Harris and M. Stephen, “A Combined Corner and Edge Detector,” Proc. 4th
Alvey Vision Conf., pp.147-151, 1988.
[20] F. Hartung and B. Girod, “Digital watermarking of MPEG-2 coded video in the bitstream
domain,” Proc. IEEE Intl. Conf. Acoustics, Speech and Signal Processing,
Vol. 4, pp. 2621-2624, 1997.
[21] F. Hartung and B. Girod, “Watermarking of Uncompressed and Compressed
Video,” Signal Processing, Vol. 66, No. 3, pp. 283-302, 1998.
[22] A. J. Hayter, “Probability and Statistics for Engineers and Scientists,” PWS Publishing
Company, 1995.
[23] J. R. Hernandez and F. Perez-Gonzalez, “Statistical Analysis of Watermarking
Schemes for Copyright Protection of Images,” Proc. IEEE, Vol. 87, pp. 1142-1143,
1999.
[24] A. Herrigel, S. Voloshynovskiy, Y. Rytsar, “The Watermark Template Attack,”
Proc. SPIE Security and Watermarking of Multimedia Contents III (Vol. 4314),
San Jose, 2001.
[25] L. W. Kang and C. S. Lu, “Low-Complexity Wyner-Ziv Video Coding Based on
Robust Media Hashing,” Proc. IEEE Int. Workshop on Multimedia Signal Processing,
Canada, 2006.
[26] L. W. Kang and C. S. Lu, “Wyner-Ziv Video Coding with Coding Mode Hidingbased
Motion Compensation,” Proc. IEEE Int. Conf. on Image Processing, USA,
2006.
[27] H. S. Kim and H. K. Lee, “Invariant Image Watermark Using Zernike Moments,”
IEEE Trans. on Circuits and Systems for Video Technology, Vol. 13, No. 8, pp.
766-775, 2003.
[28] D. Kirovski and F. A. Petitolas, “Blind Pattern Matching Attack on Watermarking
Systems,” IEEE Trans. Signal Processing, Vol. 51, pp. 1045-1053, 2003.
[29] C. Kotropoulos and I. Pitas, “Rule-based Face Detection in Frontal Views,” Proc.
IEEE ICASSP, Vol. 4, pp. 2537-2540, 1997.
[30] D. Knuth, “The Art of Computer Programming,” 3rd ed. Vol. 2, Reading, Mass.:
Addison-Wesley, 1997.
[31] D. Kundur and K. Karthik, “Video Fingerprinting and Encryption Principles for
Digital Rights Management,” Proceedings of the IEEE, Vol. 92, No. 6, pp. 918-
932, 2004.
[32] M. Kutter, “Watermarking Resisting to Translation, Rotation and Scaling,” Proc.
SPIE International Symposium on Voice, Video, and Data Communication, Boston,
1998.
[33] M. Kutter, S. K. Bhattacharjee, and T. Ebrahimi, “Toward Second Generation Watermarking
Schemes,” Proc. IEEE Int. Conf. on Image Processing, Vol. I, pp. 320-
323, 1999.
[34] M. Lee, S. Nepal, and U. Srinivasan, “Role of Edge Detection in Video Semantics,”
Proc. ACS Conferences in Research and Practice in Information Technology, Vol.
22, pp. 59-68, 2003.
[35] B. Li, E. Chang, and C. T. Wu, “DPF – A Perceptual Distance Function for Image
Retrieval,” Proc. IEEE Int. Conf. on Image Processing, Vol. 2, pp. II-597-II-600,
2002.
[36] C. Y. Lin and S. F. Chang, “A Robust Image Authentication Method Distinguishing
JPEG Compression from Malicious Manipulation,” IEEE Trans. on Circuits and
Systems for Video Tech., Vol. 11, No. 2, pp. 153-168, 2001.
[37] E. Lin, C. Podilchuk, T. Talker, and E. Delp, “Streaming Video and Rate Scalable
Compression: What Are The Challenges ForWatermarking? ” Proc. SPIE Security
and Watermarking of Multimedia Contents III, Vol. 4314, pp. 116-127, San Jose,
2001.
[38] E. Lin, C. Podilchuk, T. Talker, and E. Delp, “Temporal Synchronization in Video
Watermarking, ” Proc. SPIE Security and Watermarking of Multimedia Contents
IV, Vol. 4675, pp. 478-490, San Jose, January, 2002.
[39] C. Y. Lin, M. Wu, J. A. Bloom, I. J. Cox, M. L. Miller, and Y. M. Lui, “Rotation,
Scale and Translation Resilient Watermarking for Images,” IEEE Trans. Image
Processing, Vol. 10, No. 5, pp. 767-782, 2001.
[40] C. Y. Lin, D. Sow, and S. F. Chang, “Using Self-Authentication-and-Recovery Images
for Error Concealment in Wireless Environments,” SPIE ITCom/OptiComm,
Vol. 4518, pp. 267-274, 2001.
[41] Y. J. Liang, J. G. Apostolopoulos, and B. Girod, “Analysis of Packet Loss for Compressed
Video: Does Burst-length Matter?” Proc. IEEE Int. Conf. on Acoustics,
Speech, and Signal Processing , 2003.
[42] C. S. Lu, “Wireless Multimedia Error Resilience via A Data Hiding Technique,”
Proc. 5th IEEE Int. Workshop on Multimedia Signal Processing, pp. 316-319 ,
2002.
[43] C. S. Lu, H. Y. Liao, and M. Kutter, “Denoising and Copy Attacks ResilientWatermarking
by Exploiting Knowledge at Detector,” IEEE Trans. on Image Processing,
Vol. 11, No. 3, pp. 280-292, 2002.
[44] C. S. Lu and H. Y. Mark Liao, “Structural Digital Signature for Image Authentication:
An Incidental Distortion Resistant Scheme,” IEEE Trans. on Multimedia,
Vol. 5, No. 2, pp. 161-173, 2003.
[45] C. S. Lu and C. Y. Hsu, “Geometric Distortion-Resilient Image Hashing Scheme
and Its Applications on Copy Detection and Authentication,” ACM Multimedia
Systems Journal, special issue on Multimedia and Security, Vol. 11, No. 2, pp.
159-173, 2005.
[46] C. S. Lu, J. R. Chen, and K. C. Fan, “Real-Time Frame-Dependent Video Watermarking
in VLC Domain,” Signal Processing: Image Communication, Vol. 20, No.
7, pp. 624-642, 2005.
[47] C. S. Lu and C.Y. Hsu, “Content-Dependent Anti-Disclosure Image Watermark,”
Proc. 2nd Int. Workshop on Digital Watermarking, LNCS 2939, pp. 61-76, Seoul,
Korea, 2003.
[48] C. S. Lu, S. W. Sun, and P. C. Chang, “Robust Mesh-based Content-dependent
Image Watermarking with Resistance to Both Geometric Attack and Watermark-
Estimation Attack,” Proc. SPIE: Security, Steganography, and Watermarking of
Multimedia Contents VII (EI120), pp. 147-163, San Jose, California, USA, 2005.
[49] C. S. Lu, “Towards Robust Image Watermarking: Combining Content-Dependent
Watermark, Moment Normalization, and Side-Informed Embedding,” Signal
Processing: Image Communication, Vol. 20, No. 2, pp. 129-150, 2005.
[50] C. S. Lu and C. M. Yu, “On the Security of Mesh-based Media Hash-dependent
Watermarking Against Protocol Attacks,” Proc. IEEE Int. Conf. on Multimedia
and Expo, The Netherlands, 2005.
[51] C. S. Lu and C. Y. Hsu, “Geometric Distortion-Resilient Image Hashing Scheme
and Its Applications on Copy Detection and Authentication,” ACM Multimedia
Systems Journal, special issue on Multimedia and Security, Vol. 11, No. 2, pp.
159-173, 2005.
[52] C. S. Lu, S. W. Sun, C. Y. Hsu, and P. C. Chang, “Media Hash-dependent Image
Watermarking Resilient Against Both Geometric Attacks and Estimation Attacks
Based on False Positive-Oriented Detection,” IEEE Trans. on Multimedia, Vol. 8,
No. 4, pp. 668-685, 2006.
[53] B. M. Macq and J. J. Quisquater, “Cryptology for digital TV broadcasting,” Proceedings
of the IEEE, Vol. 83, No. 6, pp. 944-957, 1995.
[54] A. R. Manuel and P. G. Fernando, “Analysis of Pilot-based Synchronization Algorithms
for Watermarking of Still Images,” Signal Processing: Image Communication,
Vol. 17, pp. 611-633, 2002.
[55] Y. Mao and M.Wu, “Security Evaluation for Communication-Friendly Multimedia
Encryption,” Proc. IEEE Intl. Conf. Image Processing, 2004.
[56] Y. Mao and M. K. Mihcak, “Collusion-Resistant Intentional De-Synchronization
for Digital Video Fingerprinting,” submitted to IEEE Trans. on Image Processing,
Dec. 2005, preliminary version was published in Proc. IEEE Intl. Conf. Image
Processing, 2005.
[57] K. Mikolajczyk and C. Schmid, “An Affine Invariant Interest Point Detector,” Proc.
ECCV, LNCS 2350, pp. 128-142, 2002.
[58] I. Moccagatta, A. Soudagar, J. Liang, and H. Chen, “Error-Resilient Coding in
JPEG-2000 and MPEG-4,” IEEE Journal on Selected Area in Communications,
Vol. 18, No. 6, pp. 899-914, 2000.
[59] A. Nikolaidis and I. Pitas, “Region-based Image Watermarking,” IEEE Trans. on
Image Processing, Vol. 10, No. 11, pp. 1726-1740, 2001.
[60] A. Ortega and K. Ramchandran, “Rate-distortion methods for image and video
compression,” IEEE Signal Processing Magazine, Vol. 15, pp. 23-50, 1998.
[61] J. O’Ruanaidh and T. Pun, “Rotation, Scale and Translation Invariant Spread Spectrum
Digital ImageWatermarking,” Signal Processing, Vol.66, No. 3, pp. 303-317,
1998.
[62] S. Pereira, T. Pun, “Robust Template Matching for Affine Resistant Image Watermarks,”
IEEE Trans. Image Processing, Vol. 9, No. 6, pp. 1123-1129, 2000.
[63] S. Pereira, T. Pun, “An Iterative Template Matching Algorithm Using the Chirp-
Z Transform for Digital Image Watermarking,” Pattern Recognition , Vol. 33, pp.
173-175, 2000.
[64] F. Petitcolas, R. J. Anderson, and M. G. Kuhn, “Attacks on Copyright Marking
Systems,” Proc. Int. Workshop on Information Hiding, LNCS 1575, pp. 219-239,
1998.
[65] F. Petitcolas, “Watermarking Schemes Evaluation,” IEEE Signal Processing Magazine,
Vol. 17, No. 5, pp. 58-64, 2000.
[66] W. Pongpadpinit and A. Pearmain, “Recovery of Motion Vectors for Error Concealment
Based on an Edge-Detection Approach,” IEE Proc.-Vis. Image Signal
Process., Vol. 153, No. 1, pp. 63-69, 2006.
[67] R. Puri, K. Ramchandran, K. W. Lee, and V. Bharghavan, “Forward Error Correction
(FEC) Codes Based Multiple Description Coding for Internet Video Streaming
and Multicast,” Signal Processing: Image Communication, Vol. 16, pp. 745-762,
2001.
[68] M. Ramkumar and A. N. Akansu, “A Robust Scheme for Oblivious Detection of
Watermarks/Data Hiding in Still Images,” Proc. SPIE Multimedia Systems and Applications,
Vol. 3528, pp. 474-481, 1998.
[69] N. K. Ratha, J. H. Connell, and R. M. Bolle, “Enhancing Security and Privacy in
Biometrics-based Authentication Systems,” IBM Systems Journal, Vol. 40, No. 3,
pp. 614-634, 2001.
[70] K. C. Roh, K. D. Seoa, and J. K. Kim “Data Partitioning and Coding of DCT
Coefficients Based on Requantization for Error-Resilient Transmission of Video,”
Signal Processing: Image Communication, Vol. 17, pp. 573-585, 2002.
[71] A. Sehgal, A. Jagmohan, and N. Ahuja, “Wyner-Ziv Coding of Video: An Error-
Resilient Compression Framework,” IEEE Trans. on Multimedia, Vol. 6, No. 2, pp.
249-258, 2004.
[72] J. S. Seo and C. D. Yoo, “Localized Image Watermarking Based on Feature Points
of Scale-Space Representation,” Pattern Recognition, Vol. 37, pp. 1365-1375,
2004.
[73] T. Shanableh and M. Ghanbari, “Loss Concealment Using B-Pictures Motion Information,”
IEEE Trans. on Multimedia, Vol. 5, No. 2, pp. 249-258, 2003.
[74] C. Shi and B. Bhargava, “A fast MPEG video encryption algorithm,” Proc. ACM
Conf. on Multimedia, pp. 81-88, 1998.
[75] S. Shirani, F. Kossentini, and R. Ward, “A Concealment method for Video Communications
in an Error-Prone Environment”, IEEE Journal on Selected Areas in
Communications, Vol. 18, No. 6, pp. 1122-1128, 2000.
[76] D. Simitopoulos, D. E. Koutsonanos, and M. G. Strintzis, “Robust Image Watermarking
Based on Generalized Radon Transformations,” IEEE Trans. on Circuits
and Systems for Video Technology, Vol. 13, No. 8, pp. 732-745, 2003.
[77] V. Solachidis and I. Pitas, “Circularly Symmetric Watermark Embedding in 2-D
DFT Domain,” IEEE Trans. on Image Processing, Vol. 10, No. 11, pp. 1741-1753,
2001.
[78] J. Song and K. J. R. Liu, “A Data Embedded Video Coding Scheme for Error-Prone
Channels,” IEEE Trans. on Multimedia, Vol. 3, No. 4, pp. 415-423, 2001.
[79] S. Stankovic, I. Djurovic, and I. Pitas, “Watermarking in the Space/Spatial-
Frequency Domain Using Two-Dimensional Radon-Wigner Distribution,” IEEE
Trans. on Image Processing, Vol. 10, No. 4, pp. 650-658, 2001.
[80] H. Stark, J. W. Woods, “Probability and Random Processes with Applications to
Signal Processing,” Prentice Hall, 3/e, New Jersey, 2002.
[81] K. Su, D. Kundur, and D. Hatzinakos, “Statistical Invisibility for Collusionresistant
Digital Video Watermarking,” IEEE Transactions on Multimedia, Vol. 7,
No. 1, pp. 43-51, 2005.
[82] K. Su, D. Kundur, and D. Hatzinakos, “Spatially Localized Image-dependent Watermarking
for Statistical Invisibility and Collusion Resistance,” IEEE Transactions
on Multimedia, Vol. 7, No. 1, pp. 52-66, 2005.
[83] S.W. Sun, J. R. Chen, C. S. Lu, and P. C. Chang, “Video JET: Packet Loss-Resilient
Video Joint Encryption and Transmission based on Media-Hash-Embedded Residual
Data,” submitted to IEEE Trans. on Circuits and Systems for Video Technology.,
Feb. 2007, preliminary version was published in Proc. SPIE Conf. Electronic Imaging,
San Jose, CA, USA, 2006.
[84] M. D. Swanson, B. Zhu, and A. T. Tewifk, “Multiresolution Scene-based Video
Watermarking Using Perceptual Models,” IEEE J. Select. Areas Commun., Vol. 16,
pp. 540-550, 1998.
[85] C.W. Tang and H. M. Hang, “A Feature-Based Robust Digital ImageWatermarking
Scheme,” IEEE Trans. Signal Processing, Vol. 51, No. 4, pp.950-958, 2003.
[86] A. Tosun and W. C. Feng, “On Error Preserving Encryption Algorithms for Wireless
Video Transmission,” Proc. ACM Conf. on Multimedia, pp. 302-308, 2001.
[87] W. Trappe, M. Wu, and K. J. R. Liu, “Collusion-resistant Fingerprinting for Multimedia,”
Proc. IEEE Intl. Conf. Acoustics, Speech and Signal Processing, Vol. 4,
pp. 3309-3312, 2002.
[88] W. Trappe, M.Wu, Z. J.Wang, and K. J. R. Liu, “Anti-collusion Fingerprinting for
Multimedia,” IEEE Trans. Signal Processing, Vol. 51, pp. 1069-1087, 2003.
[89] S. Tsekeridou and I. Pitas, “MPEG-2 Error Concealment Based on Block-Matching
Principles,” IEEE Trans. on Circuits and System for Video Technology, Vol. 10, No.
4, pp. 646-658, 2000.
[90] S.Voloshynovskiy, A.Herrigel, N.Baumgartner and T.Pun, “A Stochastic Approach
to Content Adaptive Digital Image Watermarking,” Proc. Int. Workshop on Information
Hiding, LNCS 1768, pp. 211-236, 1999.
[91] S. Voloshynovskiy, F. Deguillaume, and T. Pun, “Multibit Digital Watermarking
Robust Against Local Nonlinear Geometrical Distortions,” Proc. IEEE Int. Conf.
Image Processing, Thessaloniki, pp. 999-1002, 2001.
[92] S. Voloshynovskiy, S. Pereira, V. Iquise, and T. Pun, “Attack Modeling: Towards
a Second Generation Watermarking Benchmark,” Signal Processing, Vol. 81, pp.
1177-1214, 2001.
[93] Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image Quality Assessment:
From Error Visibility to Structural Similarity,” IEEE Trans. on Image
Processing, Vol. 13, No. 4, pp. 600-612, 2004.
[94] J. Wen, M. Severa, W. Zeng, M. H. Luttrell, and W. Jin, “A Format-compliant
Configurable Encryption Framework for Access Control of Video,” IEEE Trans.
on Circuits and Systems for Video Technology, Vol. 12, No. 6, pp. 545-557, 2002.
[95] M. Wu, W. Trappe, Z. J. Wang, and K. J. R. Liu, “Collusion-Resistant Fingerprinting
for Multimedia,” IEEE Signal Processing Magazine, pp. 15-27, 2003.
[96] X. Xu, S. Dexter, and A. M. Eskicioglu, “A Hybrid Scheme of Encryption and
Watermarking,” IS&T/SPIE Symposium on Electronic Imaging 2004, Security,
Steganography, and Watermarking of Multimedia Contents VI Conference, Vol.
5306, pp. 725-736, 2004.
[97] G. Yang and T.S. Huang, “Human Face Detection in Complex Background,” Pattern
Recognition, Vol. 27, no. 1, pp. 53-63, 1994.
[98] M. H. Yang, D. J. Krieman, and N. Ahuja, “Detection Faces in Images: A Survey,”
IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 24, No. 1, pp. 34 -58,
2002.
[99] P. Yin, M. Wu, and B. Liu, “A Robust Error Resilient Approach for MPEG
Video Transmission over Internet,” Proc. SPIE: Visual Communication and Image
Processing, Vol. 4671, pp. 103-111, 2002.
[100] H. Zhao, M. Wu, Z.J. Wang, and K. J. R. Liu, “Nonlinear Collusion Attacks on
Independent Fingerprints for Multimedia,” Proc. IEEE Intl. Conf. Acustic, Speech,
Signal Processing 2003, pp. I-613-I-616, 2003.
[101] H. Zhao and K. J. R. Liu, “Fingerprint Multicast in Secure Video Streaming,” IEEE
Trans. Image Processing, Vol. 15, No. 1, pp. 12-28, 2006.
[102] W. Zeng and S. Lei, “Efficient Frequency Domain Selective Scrambling of Digital
Video,” IEEE Trans. on Multimedia, Vol. 5, No. 1, pp. 118-129, 2003.
[103] D. Zheng, J. Zhao, and A. El Saddik, “RST-Invariant Digital Image Watermarking
Based on Log-Polar Mapping and Phase Correlation,” IEEE Trans. on Circuits and
Systems for Video Technology, Vol. 13, No. 8, pp. 753-765, 2003.
[104] W. Zeng, X. Zhuang, and J. Lan, “Network Friendly Media Security: Rationales,
Solutions, and Open Issues,” Proc. IEEE Int. Conf. on Image Processing, Vol. 1,
pp. 565-568, 2004.
[105] P. Zhu and P. M. Chirlian, “On Critical Point Detection of Digital Shapes,” IEEE
Trans. Pattern Analysis and Machine Intelligence, Vol. 17, No. 8, pp. 737-748,
1995.
[106] B. B. Zhu, M. D. Swanson, A. H. Tewfik, “When seeing isn’t believing [multimedia
authentication technologies],” IEEE Signal Processing Magazine, Vol. 21, No. 2,
pp. 40-49, 2004.
[107] B. B. Zhu, C. Yuan, Y. Wang and S. Li, “Scalable Protection for MPEG-4 Fine
Granularity Scalability,” IEEE Trans. on Multimedia, Vol. 7, No. 2, pp. 222-233,
2005.
指導教授 張寶基、呂俊賢
(Pao-Chi Chang、Chun-Shien Lu)
審核日期 2007-7-2
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