叛徒追踪的多媒体指纹取证（K. J. Liu）Multimedia Fingerprinting Forensics for T....pdf

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s Multimedia i Fingerprinting Forensics for Traitor Tracing K. J. Ray Liu, Wade Trappe, Z. Jane Wang, Min Wu, and Hong Zhao n o i t a c n u m m o C d n a g n s s e c o r P i i l a n g S n o s e i r e S k o o B P S A R U E I

Multimedia Fingerprinting Forensics for Traitor Tracing

EURASIP Book Series on Signal Processing and Communications, Volume 4 Multimedia Fingerprinting Forensics for Traitor Tracing K. J. Ray Liu, Wade Trappe, Z. Jane Wang, Min Wu, and Hong Zhao Hindawi Publishing Corporation http://www.hindawi.com

EURASIP Book Series on Signal Processing and Communications Editor-in-Chief: K. J. Ray Liu Editorial Board: Zhi Ding, Moncef Gabbouj, Peter Grant, Ferran Marqu´es, Marc Moonen, Hideaki Sakai, Giovanni Sicuranza, Bob Stewart, and Sergios Theodoridis Hindawi Publishing Corporation 410 Park Avenue, 15th Floor, #287 pmb, New York, NY 10022, USA Nasr City Free Zone, Cairo 11816, Egypt Fax: +1-866-HINDAWI (USA Toll-Free) © 2005 Hindawi Publishing Corporation All rights reserved. No part of the material protected by this copyright notice may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without written permission from the publisher. ISBN 977-5945-18-6

Dedication To Our Families

Contents Preface 1. Introduction 2. Preliminaries on data embedding 2.1. Content protection via digital watermarking 2.1.1. Major applications and design requirements 2.1.2. Basic embedding approaches 2.2. Robust additive spread-spectrum embedding 2.2.1. Overview of spread-spectrum embedding 2.2.2. Distortion and attacks against robust embedding 2.2.3. Mathematical formulation 2.2.4. Alternative detection statistics 2.2.5. Exploiting human visual properties 2.3. Employing spread-spectrum embedding in ﬁngerprinting 3. Collusion attacks 3.1. 3.2. Introduction to collusion attacks 3.1.1. Linear collusion attacks 3.1.2. Nonlinear collusion attacks Introduction to order statistics 3.2.1. Distribution of order statistics 3.2.2. 3.2.3. Joint distribution of two diﬀerent order statistics Joint distribution of order statistics and the unordered random variables 3.3. Multimedia ﬁngerprinting system model 3.4. 3.3.1. Fingerprinting systems and collusion attacks 3.3.2. Performance criteria Statistical analysis of collusion attacks 3.4.1. Analysis of collusion attacks 3.4.2. Analysis of detection statistics System performance analysis 3.4.3. 3.5. Collusion attacks on Gaussian-based ﬁngerprints 3.5.1. Unbounded Gaussian ﬁngerprints 3.5.2. Bounded Gaussian-like ﬁngerprints 3.6. Preprocessing of the extracted ﬁngerprints 3.7. Experiments with images 3.8. Chapter summary xi 1 7 7 8 9 11 12 13 15 17 21 23 25 26 26 28 29 30 30 31 33 33 35 36 36 41 42 43 43 48 52 57 61

viii Contents 4. Orthogonal ﬁngerprinting and collusion resistance 4.1. Collusion resistance analysis 4.1.1. The maximum detector 4.1.2. The thresholding detector 4.2. Extensions to other performance criteria 4.3. Extensions to other types of attacks 4.4. A practical estimator for the amount of colluders 4.5. Experiments with images 4.6. Eﬃcient ﬁngerprint detection using tree structure 4.6.1. Tree-structured detection strategy 4.6.2. Experiments on tree-based detector 4.7. Chapter summary 5. Group-oriented ﬁngerprinting 5.1. Motivation for group-based ﬁngerprinting 5.2. Two-tier group-oriented ﬁngerprinting system 5.2.1. Fingerprint design scheme 5.2.2. Detection scheme 5.2.3. Performance analysis 5.3. Tree-structure-based ﬁngerprinting system 5.3.1. Fingerprint design scheme 5.3.2. Detection scheme 5.3.3. Parameter settings and performance analysis 5.4. Experimental results on images 5.5. Chapter summary 6. Anticollusion-coded (ACC) ﬁngerprinting 6.1. Prior work on collusion-resistant ﬁngerprinting for generic data 6.2. Code modulation with spread-spectrum embedding 6.3. Combinatorial designs 6.4. Combinatorial-design-based anticollusion codes 6.4.1. Formulation and construction of ACC codes 6.4.2. Examples of BIBD-based ACC 6.4.3. ACC coding eﬃciency and BIBD design methods 6.5. Detection strategies and performance tradeoﬀs 6.5.1. Hard detection 6.5.2. Adaptive sorting approach 6.5.3. Sequential algorithm 6.6. Experimental results for ACC ﬁngerprinting 6.6.1. ACC simulations with Gaussian signals 6.6.2. ACC experiments with images 6.7. A uniﬁed formulation on ﬁngerprinting strategies 6.8. Chapter summary 7. Secure ﬁngerprint multicast for video streaming 7.1. Secure video streaming 63 65 66 68 78 83 88 90 94 94 98 99 101 102 105 105 106 111 121 121 122 124 132 135 137 139 142 143 148 149 150 152 154 156 157 157 158 158 163 164 168 171 172

Contents 7.2. Prior art in secure ﬁngerprint multicast 7.3. General ﬁngerprint multicast distribution scheme 7.4. Joint ﬁngerprint design and distribution scheme 7.4.1. Comparison of ﬁngerprint modulation schemes 7.4.2. Joint ﬁngerprint design and distribution 7.4.3. Addressing the computation constraints 7.5. Analysis of bandwidth eﬃciency “Multicast only” scenario 7.5.1. 7.5.2. General ﬁngerprint multicast scheme 7.5.3. Joint ﬁngerprint design and distribution scheme 7.6. Robustness of the embedded ﬁngerprints 7.6.1. Digital ﬁngerprinting system model 7.6.2. Performance criteria 7.6.3. Comparison of collusion resistance 7.7. Fingerprint drift compensation 7.8. Chapter summary 8. Fingerprinting curves Introduction 8.1. 8.2. Basic embedding and detection 8.3. 8.2.1. Feature extraction 8.2.2. Fingerprinting in the control-point domain 8.2.3. Fidelity and robustness considerations 8.2.4. Experiments with simple curves Iterative alignment-minimization algorithm for robust ﬁngerprint detection 8.3.1. Problem formulation 8.3.2. 8.3.3. Detection example and discussion Iterative alignment-minimization algorithm 8.4. Experiments with maps 8.5. Chapter summary Bibliography Index ix 173 174 176 177 180 185 186 186 187 191 194 194 195 195 199 202 205 205 208 208 210 212 215 219 221 222 225 228 237 239 251

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叛徒追踪的多媒体指纹取证（K. J. Liu）Multimedia Fingerprinting Forensics for T....pdf

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