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Research Overview
Research Overview
Research Overview
Research Overview
Research Overview
Research Overview
Research Overview
Research Overview
Research Overview
Research Overview
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Research Overview

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

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