簡易檢索 / 詳目顯示

研究生: 周家愷
Jia-Kai Chou
論文名稱: 具隱私性考量之多媒體資料處理
Privacy Preserving Multimedia Data Processing
指導教授: 楊傳凱
Chuan-Kai Yang
口試委員: 鍾國亮
Kuo-Liang Chung
歐陽明
Ming Ouhyoung
闕志克
Tzi-cker Chiueh
吳宗成
none
學位類別: 博士
Doctor
系所名稱: 管理學院 - 資訊管理系
Department of Information Management
論文出版年: 2013
畢業學年度: 101
語文別: 英文
論文頁數: 92
中文關鍵詞: 具隱私性考量的以區塊為基礎之轉換演算法影像捲積影像/影片檢索容積資料呈像
外文關鍵詞: Privacy Preserving, Block-based Transformation Algorithm, Image Convolution, Image/Video Retrieval, Volume Rendering.
相關次數: 點閱:279下載:0
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 由於科技的進步,更尤其雲端運算技術的興起,不論是個人還是企業,每天都有大量的數位資料被產生並傳送到雲端的伺服器儲存,以達到無時無刻,任何地方皆可取得資料及使用的最大彈性。
    在資料被代管的同時,如何保護資料的隱私一直都是被廣泛討論的議題。本論文將針對三種多媒體資料的隱私性保護進行討論:影像(images)、影片(videos)及容積資料(volume datasets)。這些資料的共同特性是相較於一般檔案,如文字檔,通常需要較大的儲存空間。因此,傳統加密方式套用到這類資料時,可能會有執行效率的問題。此外,若對加密過後的資料進行複雜的操作時,可能產生明顯的誤差,導致計算結果不精確。基於以上考量,我們採用一種稱為「以區塊為基礎之轉換演算法」(block-based transformation algorithm)來保護資料的內容。
    除了隱私性的考量,我們也希望在對被保護的資料做分析或操作的同時,可以大量借助遠端伺服器的運算能力,以減輕使用者端的負擔。以下幾項對多媒體資料處理的功能可在本論文所提出的架構上達成:影像捲積(image convolution)、影像/影片檢索(image/video retrieval)及容積資料視覺化(volume visualization)。
    實驗的結果顯示,我們提出的方法在資料保護和處理效能以及運算的誤差之間取得一個很好的平衡。更重要的是,我們所提出的將容積資料在考量隱私性的情況下進行呈像也為該研究領域增添更多可能性並提供了新的研究方向。


    Nowadays, enormous amount of digital data is transmitted and stored to remote servers. How to preserve the privacy of the data deposited on remote servers has then become a major concern when sensitive information needs to be protected.
    In this dissertation, the preservation of the privacy on three types of digital data is discussed, i.e. images, videos, and volume datasets. These types of data basically consume bigger storage capacity when compared with ordinary ones, e.g. textual data. Applying traditional cryptographic encryption methods may not be as efficient and practical as desired. In addition, when some processing or operation of data is involved, potential noises or errors may occur due to complicated computations required. Therefore, an alternative, block-based transformation algorithm, is adopted for maintaining the privacy of data from unauthorized viewers.
    Other than protecting the privacy of data, it is also critical if the computation effort can be delegated to the servers as much as possible while operations are to be applied on the remotely stored and protected data. In this regard, several functionalities are provided under the proposed privacy preserving mechanism, i.e. convolutional image processing, image/video retrieval, and volume visualization.
    Experimental results show that the proposed approach strikes a good balance between quality and performance in terms of the involved operations. Furthermore, privacy-preserving volume rendering has been made possible, and to the best of our knowledge, there is no previous research similarly addressing this privacy issue.

    摘要 I ABSTRACT II 致謝 III TABLE OF CONTENT V LIST OF FIGURES VIII LIST OF TABLES XIV Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Contributions 3 1.3 Organization 4 Chapter 2 Related Work 5 2.1 Preserving Privacy of Multimedia Data 5 2.1.1. Image/Video Content Protection 5 2.1.2. 3D Volume Data Protection 6 2.2 Convolutional Image Processing and Image/Video Retrieval 7 2.2.1. General Image Convolution 7 2.2.2. Privacy Preserving Convolutional Image Processing 7 2.2.3. General Image/Video Retrieval 8 2.2.4. Privacy Preserving Image/Video Retrieval 10 2.3 Visualization 11 2.3.1. Volume Rendering 11 2.3.2. Privacy Preserving Visualization 11 Chapter 3 Block-based Image/Video Transformation 13 3.1 Image Transformation Scheme 13 3.2 Transformation Key Configuration 18 Chapter 4 Privacy Preserving Convolutional Image Processing and Image/Video Retrieval 21 4.1 Privacy Preserving Convolutional Image Processing 21 4.2 Privacy Preserving Image Retrieval 23 4.3 Privacy Preserving Video Retrieval 28 Chapter 5 Block-based Volume Data Transformation 30 5.1 Volume Data Transformation Scheme 30 5.2 Transformation Key Configuration 34 Chapter 6 Privacy Preserving Volume Rendering 35 6.1 Privacy Aware Transfer Function Adjustment 35 6.2 Remote Rendering and Local Compositing 40 Chapter 7 Results and Discussion 43 7.1 Image/Video Data Transformation 43 7.1.1. Datasets 43 7.1.2. Transformation and Inverse Transformation Results 44 7.1.3. Storage Overhead Analysis 47 7.1.4. Timing Analysis 49 7.1.5. Degree of Privacy Analysis 51 7.1.6. Limitation 56 7.2 Privacy Preserving Image Convolution 59 7.3 Privacy Preserving Image/Video Retrieval 62 7.3.1. Privacy Preserving Image Retrieval 62 7.3.2. Privacy Preserving Video Retrieval 67 7.4 3D Volume Data Transformation 69 7.4.1. Degree of Privacy Analysis 71 7.4.2. Enhancing the Degree of Privacy 74 7.4.3. Limitation 75 7.5 Privacy Preserving Volume Rendering 77 7.5.1. Rendering Quality 77 7.5.2. Degree of Privacy Analysis 80 7.5.3. Enhancing the Degree of Privacy 82 7.5.4. Limitation 82 Chapter 8 Conclusions and Future Work 83 8.1 Conclusions 83 8.2 Future work 84 8.2.1. Watermarking 84 8.2.2. Enhancing Flexibility 84 8.2.3. Others 85 References 86 Appendix 92

    [APG94] N. AKROUT, R. PROST, and R. GOUTTE, “Image Compression by Vector Quantization: A Review Focused on Codebook Generation”, Image and Vision Computing, vol. 12, no. 10, pages 627–637, 1994.
    [AS00] R. Agrawal and R. Srikant. Privacy-preserving data mining. ACM Sigmod Record, vol. 29, no. 2, pages 439–450, 2000.
    [Bob01] M. Bober, “MPEG-7 Visual Shape Descriptor,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 11, no. 6, pages 716 – 719, 2001.
    [CBCB08] M. Cancellaro, F. Battisti, M. Carli, G. Boato, F. G. B. D. Natale, and A. Neri, “A Joint Digital Watermarking and Encryption Method,” in SPIE, vol. 6819, 2008, page 68191C.
    [CBCB11] M. Cancellaro, F. Battisti, M. Carli, G. Boato, F. G. B. D. Natale, and A. Neri, “A Commutative Digital Image Watermarking and Encryption Method in the Tree Structured Haar Transform Domain,” Signal Processing: Image Communication, vol. 26, no. 1, pages 1–12, 2011.
    [DCH88] R. A. Drebin, L. Carpenter and P. Hanrahan, “Volume Rendering,” Computer Graphics, vol. 22, no. 4, pages 65 – 74, 1988.
    [DD07] E. D. Demaine and M. L. Demaine, “Jigsaw Puzzles, Edge Matching, and Polyomino Packing: Connections and Complexity,” Graphs and Combinatorics, vol. 23, pages 195–208, 2007.
    [Dev87] J. L. Devore, “Probability and Statistics for Engineering and the Sciences”, 2nd ed. Brooks/Cole Publishing Company, 1987.
    [DKN08] T. Deselaers, D. Keysers, and H. Ney, “Features for image retrieval: an experimental comparison,” Journal of Image Retrieval, vol. 11, no. 2, pages 77–107, 2008.
    [DK11] A. Dasgupta and R. Kosara, “Adaptive Privacy-Preserving Visualization using Parallel Coordinates, ” IEEE Transactions on Visualization and Computer Graphics, vol. 17, no.12, pages 2241–2248, 2011.
    [DK11-2] A. Dasgupta and R. Kosara, “Privacy-Preserving Data Visualization using Parallel Coordinates,” Visualization and Data Analysis, 2011, pages 78680O-1–78680O-12.
    [EPKL07] Z. Erkin, A. Piva, S. Katzenbeisser, R. L. Lagendijk, J. Shokrollahi, G. Neven, and M. Barni, “Protection and Retrieval of Encrypted Multimedia Content: When Cryptography Meets Signal Processing,” EURASIP Journal on Information Security, vol. 7, no. 2, pages 1–20, 2007.
    [FG07] C. Fontaine and F. Galand, “A survey of homomorphic encryption for nonspecialists,” EURASIP Journal on Information Security, vol. 2007, no. 15, pages 1 – 15, 2007.
    [FY38] R. A. Fisher and F. Yates, “Statistical Tables for Biological, Agricultural and Medical Research,” 3rd ed., London: Oliver & Boyd, 1938.
    [Gen10] C. Gentry, “Computing Arbitrary Functions of Encrypted Data,” Communications of the ACM, vol. 53, no. 3, pages 97–105, 2010.
    [GB00] A. Girgensohn and J. Boreczky, “Time-Constrained Keyframe Selection Technique,” Multimedia Tools and Applications, vol. 11, no. 3, pages 347 – 358, 2000.
    [GPG11] A. Gautam, M. Panwar, and P. Gupta, “A New Image Encryption Approach Using Block Based Transformation Algorithm,” Internationl Journal of Advanced Engineering Sciences and Technologies, vol. 8, no. 1, pages 90–96, 2011.
    [GW08] R. C. Gonzalez and R. E. Woods, “Digital Image Processing,” 3rd ed., Prentice Hall, 2008.
    [HCNY10] Z. C. Huang, P. K. Chan, W. Y. Ng, and D. S. Yeung, “Content-based Image Retrieval using Color Moment and Gabor Texture Feature,” in Proceedings of the Ninth International Conference on Machine Learning and Cybernetics, 2010, pages 719–724.
    [HLP11] C. Y. Hsu, C. S. Lu, and S. C. Pei, “Homomorphic Encryption-based Secure SIFT for Privacy-Preserving Feature Extraction,” in SPIE, vol. 7880, 2011, page 788005.
    [HXLZ11] W. Hu, N. Xie, L. Li, X. Zeng, and S. Maybank, “A Survey on Visual Content-Based Video Indexing and Retrieval,” IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS, vol. 41, no. 6, pages 797–819, 2011.
    [IKN98] L. Itti, C. Koch, and E. Niebur, “A model of saliency based visual attention for rapid scene analysis,” IEEE Transactions Pattern Analysis and Machine Intelligence, vol. 20, no. 11, pages 1254–1259, 1998.
    [JM10] A. Jolfaei and A. Mirghadri, “An Image Encryption Approach using Chaos and Stream Cipher,” Journal of Theoretical and Applied Information Technology, vol. 19, no. 2, pages 117–125, 2010.
    [JWG04] S. Jeong, C. S. Won, and R. M. Gary, “Image Retrieval using Color Histograms Generated by Gauss Mixture Vector Quantization,” Computer Vision and Image Understanding, vol. 94, no. 1-3, pages 44–66, 2004.
    [Kau91] A. Kaufman, “Volume Visualization (Tutorial),” IEEE Computer Society Press, 1991.
    [Kau96] A. Kaufman, “Volume Visualization,” ACM Computing Surveys, vol. 28, no. 1, pages 165 – 167, 1996.
    [Lev88] M. Levoy. “Display of Surfaces from Volume Data,” IEEE Computer Graphics and Applications, vol. 8, no. 3, pages 29 – 37, 1988.
    [Low99] D. G. Lowe. “Object Recognition from Local Scale-Invariant Features,” in Proceedings of the International Conference on Computer Vision, 1999, pages 1150–1157.
    [LSVW09] W. Lu, A. Swaminathan, A. L. Varna, and M. Wu, “Enabling Search Over Encrypted Multimedia Databases,” in SPIE/IS&T Media Forensics and Security, vol. 7254, no. 1. SPIE, 2009, page 725418.
    [LVSW09] W. Lu, A. L. Varna, A. Swaminathan, and M. Wu, “Secure Image Retrieval Through Feature Protection,” in IEEE Conference on Acoustics, Speech and Signal Processing, 2009, pages 1533–1536.
    [LZ09] W. Liu and C. Zhao, “Digital Watermarking for Volume Data based on 3D-DWT and 3D-DCT,” In Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human, 2009, pages 352–357.
    [MB01] S. Maniccam and N. Bourbakis, “Lossless Image Compression and Encryption using SCAN,” in Pattern Recognition, vol. 34, 2001, pages 1229–1245.
    [MKGV07] A. Machanavajjhala, D. Kifer, J. Gehrke, and M. Venkitasubramaniam, “L-diversity: Privacy beyond k-anonymity,” ACM Transactions on Knowledge Discovery from Data, vol. 1, no. 1, 2007.
    [MM96] B. Manjunath and W. Ma, “Texture Features for Browsing and Retrieval of Image Data,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, no. 8, pages 837 – 842, 1996.
    [MRP06] A. Mitra, Y. V. S. Rao, and S. R. M. Prasanna, “A New Image Encryption Approach using Combinational Permutation Techniques,” Journal of Computer Science, vol. 1, no. 1, pages 127–131, 2006.
    [PJW02] M. Park, J. S. Jin and L. S. Wilson, “Fast Content-based Image Retrieval using Quasi-Gabor Filter and Reduction of Image Feature Dimension,” In IEEE Southwest Symposium on Image Analysis and Interpretation, 2002.
    [RPTB01] Y. Rubner, J. Puzicha, C. Tomasi and J. M. Buhmann, “Empirical Evaluation of Dissimilarity Measures of Color and Texture,” Computer Vision and Image Understanding, vol. 84, no. 1, pages 25 – 43, 2001.
    [SC02] J. Shih and L. H. Chen, “Colour Image Retrieval based on Primitives of Colour Moments,” in Proceedings of the 5th International Conference on Recent Advances in Visual Information Systems, 2002, pages 88–94.
    [SRS11] N. Sharma, P. Rawat, and J. Singh, “Efficient CBIR using Color Histogram Processing,” Signal & Image rocessing : An International Journal(SIPIJ), vol. 2, no. 1, pages 94–112, 2011.
    [Swe02] L. Sweeney. “k-Anonymity: a Model for Protecting Privacy,” International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol. 10, no. 5, pages 557–570, 2002.
    [WGKH01] Y. Wu, X. Guan, M. S. Kankanhalli, and Z. Huang, “Robust Invisible Watermarking of Volume Data using the 3D DCT, ” In Computer Graphics International, 2001, pages 359–362.
    [WLW01] J. Z. Wang, J. Li, and G. Wiederhold, “Simplicity: Semantics-sensitive integrated matching for picture libraries,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, pp. 947–963, 2001.
    [WM88] L. T.Wang and E. J. McCluskey, “Linear Feedback Shift Register Design using Cyclic Codes,” IEEE Transactions on Computers, vol. 37, no. 10, pages 1302–1306, 1988.
    [YJ08] M. A. B. Younes and A. Jantan, “An Image Encryption Approach Using a Combination of Permutation Technique Followed by Encryption,” International Journal of Computer Science and Network Security, vol. 8, no. 4, pages 191–197, 2008.
    [YJLF08] C. –C. Yu, F. –D. Jou, C.-C. Lee, K. –C. Fan and T. C. Chuang, “Efficient Multi-Resolution Histogram Matching for Fast Image/Video Retrieval,” Pattern Recognition Letters 29, pages 1858–1867, 2008.
    [YK10] J. W. Yoon and H. Kim, “An Image Encryption Scheme with a Pseudorandom Permutation Based on Chaotic Maps,” Communications in Nonlinear Science and Numerical Simulation, vol. 15, no. 12, pages 3998–4006, 2010.
    [ZL02] W. Zeng and S. Lei, “Efficient Frequency Domain Selective Scrambling of Digital Video,” IEEE Transactions on Multimedia, vol. 5, pages 118–129, 2002.

    無法下載圖示 全文公開日期 2018/07/25 (校內網路)
    全文公開日期 本全文未授權公開 (校外網路)
    全文公開日期 本全文未授權公開 (國家圖書館:臺灣博碩士論文系統)
    QR CODE