Digital Fingerprinting for Multimedia Content Protection<br />Avinash L. Varna<br />Advisor: Prof. Min Wu<br />Department ...
Motivation<br />Alice<br />w1<br />w2<br />Embed Fingerprints<br />Bob<br />w3<br />Carl<br />Alice,Bob, …<br />Detect Fin...
Fingerprinting Compressed Multimedia<br />Set Top Box<br />Decrypt Decompress<br />Pirated <br />Copy<br />Compressed vide...
Anti-Collusion Dither<br />With Dither<br />Without Dither<br />Distribution of host signal at various stages<br />of the ...
Anti-Collusion Dither<br />Add a dither signal before embedding to make the host appear more continuous<br />Collusion res...
Multimedia Content Identification<br />Content Filtering<br />Metadata Services<br />From Verizon<br />Shazam for iPhone<b...
Theoretical Analysis and Results<br />Simple model : i.i.d. equiprobable fingerprint bits and noise alters each bit indepe...
Theoretical Analysis and Results<br />Simple model : i.i.d. equiprobable fingerprint bits and noise alters each bit indepe...
Contributions of the Dissertation<br />Multimedia Content Protection<br />Deterrence & Tracing<br />Identification & Filte...
Selected Publications<br />Journal Papers<br />A. L. Varna, S. He, A. Swaminathan, and M. Wu, "Fingerprinting Compressed M...
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Research Overview

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Research Overview

  1. 1. Digital Fingerprinting for Multimedia Content Protection<br />Avinash L. Varna<br />Advisor: Prof. Min Wu<br />Department of Electrical and Computer Engineering <br />University of Maryland, College Park<br />
  2. 2. Motivation<br />Alice<br />w1<br />w2<br />Embed Fingerprints<br />Bob<br />w3<br />Carl<br />Alice,Bob, …<br />Detect Fingerprints<br />Identify Content<br />ShutterIsland<br />Internet<br />Alice,Bob, …<br />Alice<br />Shutter Island<br />Bob<br />Carl<br />Embedded Fingerprints<br />Content Fingerprints<br />Collusion-resistant Fingerprint Design for Compressed Multimedia<br />Analysis of Fingerprints for Content Identification<br />
  3. 3. Fingerprinting Compressed Multimedia<br />Set Top Box<br />Decrypt Decompress<br />Pirated <br />Copy<br />Compressed video<br />Cable TV distribution system<br />Embed Fingerprint<br />Collude<br />Challenges:<br />Discrete nature of host makes embedded fingerprint vulnerable to multi-user collusion attack<br />Traditional fingerprinting: averaging ~10 copies sufficient to remove fingerprints<br />Fingerprint embedding should not significantly increase file size<br />
  4. 4. Anti-Collusion Dither<br />With Dither<br />Without Dither<br />Distribution of host signal at various stages<br />of the embedding process<br />Add a dither signal before embedding to make the host appear more continuous<br />Δ= 6<br /><ul><li>Collusion resistance increases to ~30 colluders (from ~7)</li></ul>A. L. Varna, S. He, A. Swaminathan, and M. Wu, "Fingerprinting Compressed Multimedia Signals", IEEE Transactions on Information Forensics and Security, Sep. 2009, pp 330-345.<br />
  5. 5. Anti-Collusion Dither<br />Add a dither signal before embedding to make the host appear more continuous<br />Collusion resistance increases to ~30 colluders (from ~7)<br />Theoretical Analysis:<br />More users can be accommodated under given attack<br />Difficult for attacker to estimate host accurately<br />Derived expressions for Probability of detection PD<br />Simulations using images:<br />Preserves visual quality<br />File size does not increase significantly<br />A. L. Varna, S. He, A. Swaminathan, and M. Wu, "Fingerprinting Compressed Multimedia Signals", IEEE Transactions on Information Forensics and Security, Sep. 2009, pp 330-345.<br />
  6. 6. Multimedia Content Identification<br />Content Filtering<br />Metadata Services<br />From Verizon<br />Shazam for iPhone<br />Developed framework for modeling and understanding<br />Analyze the mapping from video to features to bits:how is processing on video translated to changes in fingerprint bits?<br />Model performance at bit string level<br />Quantization & Encoding<br />Feature Extraction<br />Matching<br />Video<br />
  7. 7. Theoretical Analysis and Results<br />Simple model : i.i.d. equiprobable fingerprint bits and noise alters each bit independently with probability p<br /><ul><li>With M fingerprints of length N, to ensure Pf < εand highPd</li></ul>M = 230, ε = 2-50<br /><ul><li>Interpretation from information theory viewpoint: joint source channel coding</li></ul>A. L. Varna and M. Wu, "Theoretical Modeling and Analysis of Content Fingerprinting", submitted to the IEEE Transactions on Information Forensics and Security, Dec. 2009.<br />
  8. 8. Theoretical Analysis and Results<br />Simple model : i.i.d. equiprobable fingerprint bits and noise alters each bit independently with probability p<br />Derived guideline for choosing fingerprint length<br />Game-theoretic analysis to derive optimal strategies for attacker and detector<br />Markov Random Field model to capture correlations<br />Understand influence of correlation on detection<br />Cannot estimate rare-event probability accurately using traditional Markov Chain Monte-Carlo (MCMC) simulations<br />Use statistical physics inspired approachto compute probabilities<br />Noise<br />Original Fingerprint<br />A. L. Varna and M. Wu, "Theoretical Modeling and Analysis of Content Fingerprinting", submitted to the IEEE Transactions on Information Forensics and Security, Dec. 2009.<br />
  9. 9. Contributions of the Dissertation<br />Multimedia Content Protection<br />Deterrence & Tracing<br />Identification & Filtering<br />Collusion-resistant Fingerprints<br />Content Fingerprintsfor Identification<br />
  10. 10. Selected Publications<br />Journal Papers<br />A. L. Varna, S. He, A. Swaminathan, and M. Wu, "Fingerprinting Compressed Multimedia Signals", IEEE Transactions on Information Forensics and Security, Sep. 2009, pp 330-345.<br />A. L. Varna and M. Wu, "Theoretical Modeling and Analysis of Content Fingerprinting", submitted to the IEEE Transactions on Information Forensics and Security, Dec. 2009.<br />Wenjun Lu, A.L. Varna, AshwinSwaminathan, and Min Wu, "Privacy Preserving Multimedia Retrieval", submitted to IEEE Transactions on Information Forensics and Security, Oct. 2009, under revision.<br />A. L. Varna and M. Wu, “Game-theoretic Analysis of Content Fingerprinting”, under preparation.<br />Selected Conference Papers<br />A. L. Varna, Shan He, AshwinSwaminathan, Min Wu, Haiming Lu, and Zengxiang Lu, "Collusion-Resistant Fingerprinting for Compressed Multimedia Signals", IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 2, pp. 165 - 168, Apr. 2007.<br />A. L. Varna, AshwinSwaminathan, and Min Wu, "A Decision Theoretic Framework for Analyzing Hash-based Content Identification Systems", ACM Digital Rights Management Workshop, pp. 67-76 Oct. 2008.<br />A. L. Varna and Min Wu, "Modeling and Analysis of Content Identification", IEEE International Conference on Multimedia and Expo, pp. 1529-1531, Jun. 2009.<br />A. L. Varna, Wei-Hong Chuang, and Min Wu, "A Framework for Theoretical Analysis of Content Fingerprinting", SPIE and IS&T Media Forensics and Security, Jan. 2010.<br />
  11. 11. Contributions of the Dissertation<br />Collusion-resistant fingerprints for compressed multimedia<br />Evaluated performance of Gaussian based sequences<br />Introduced Anti-Collusion Dither that can approximately triplethe collusion resistance<br />Analyzed performance of techniques from different viewpoints<br />Analysis of multimedia content identification<br />Developed a theoretical framework for analyzing content identification schemes<br />Proposed models for binary fingerprints and derived fundamental bounds on performance<br />Performed game-theoretic analysis of interaction between the system designer and attacker<br />

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