William Puech

Multimedia Security 1 (eBook, ePUB)

Authentication and Data Hiding

• Format: ePub

Produktbeschreibung

Today, more than 80% of the data transmitted over networks and archived on our computers, tablets, cell phones or clouds is multimedia data - images, videos, audio, 3D data. The applications of this data range from video games to healthcare, and include computer-aided design, video surveillance and biometrics. It is becoming increasingly urgent to secure this data, not only during transmission and archiving, but also during its retrieval and use. Indeed, in today's "all-digital" world, it is becoming ever-easier to copy data, view it unrightfully, steal it or falsify it. Multimedia Security 1 analyzes the issues of the authentication of multimedia data, code and the embedding of hidden data, both from the point of view of defense and attack. Regarding the embedding of hidden data, it also covers invisibility, color, tracing and 3D data, as well as the detection of hidden messages in an image by steganalysis.

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Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 320
• Erscheinungstermin: 8. März 2022
• Englisch
• ISBN-13: 9781119901792
• Artikelnr.: 63584592

Autorenporträt

William Puech is Professor of Computer Science at Université de Montpellier, France. His research focuses on image processing and multimedia security in particular, from its theories to its applications.

Inhaltsangabe

Foreword by Gildas Avoine xi

Foreword by Cédric Richard xiii

Preface xv
illiam PUECH

Chapter 1 How to Reconstruct the History of a Digital Image, and of Its Alterations 1
Quentin BAMMEY, Miguel COLOM, Thibaud EHRET, Marina GARDELLA, Rafael GROMPONE, Jean-Michel MOREL, Tina NIKOUKHAH and Denis PERRAUD

1.1 Introduction 2

1.1.1 General context 2

1.1.2 Criminal background 3

1.1.3 Issues for law enforcement 4

1.1.4 Current methods and tools of law enforcement 5

1.1.5 Outline of this chapter 5

1.2 Describing the image processing chain 8

1.2.1 Raw image acquisition 8

1.2.2 Demosaicing 8

1.2.3 Color correction 10

1.2.4 JPEG compression 11

1.3 Traces left on noise by image manipulation 11

1.3.1 Non-parametric estimation of noise in images 11

1.3.2 Transformation of noise in the processing chain 13

1.3.3 Forgery detection through noise analysis 15

1.4 Demosaicing and its traces 18

1.4.1 Forgery detection through demosaicing analysis 19

1.4.2 Detecting the position of the Bayer matrix 20

1.4.3 Limits of detection demosaicing 23

1.5 JPEG compression, its traces and the detection of its alterations 23

1.5.1 The JPEG compression algorithm 23

1.5.2 Grid detection 25

1.5.3 Detecting the quantization matrix 27

1.5.4 Beyond indicators, making decisions with a statistical model 28

1.6 Internal similarities and manipulations 31

1.7 Direct detection of image manipulation 33

1.8 Conclusion 34

1.9 References 35

Chapter 2 Deep Neural Network Attacks and Defense: The Case of Image Classification 41
Hanwei ZHANG, Teddy FURON, Laurent AMSALEG and Yannis AVRITHIS

2.1 Introduction 41

2.1.1 A bit of history and vocabulary 42

2.1.2 Machine learning 44

2.1.3 The classification of images by deep neural networks 46

2.1.4 Deep Dreams 48

2.2 Adversarial images: definition 49

2.3 Attacks: making adversarial images 51

2.3.1 About white box 52

2.3.2 Black or gray box 62

2.4 Defenses 64

2.4.1 Reactive defenses 64

2.4.2 Proactive defenses 66

2.4.3 Obfuscation technique 67

2.4.4 Defenses: conclusion 68

2.5 Conclusion 68

2.6 References 69

Chapter 3 Codes and Watermarks 77
Pascal LEFEVRE, Philippe CARRE and Philippe GABORIT

3.1 Introduction 77

3.2 Study framework: robust watermarking 78

3.3 Index modulation 81

3.3.1 LQIM: insertion 81

3.3.2 LQIM: detection 82

3.4 Error-correcting codes approach 82

3.4.1 Generalities 84

3.4.2 Codes by concatenation 86

3.4.3 Hamming codes 88

3.4.4 BCH codes 90

3.4.5 RS codes 93

3.5 Contradictory objectives of watermarking: the impact of codes 96

3.6 Latest developments in the use of correction codes for watermarking 98

3.7 Illustration of the influence of the type of code, according to the attacks 102

3.7.1 JPEG compression 103

3.7.2 Additive Gaussian noise 106

3.7.3 Saturation 106

3.8 Using the rank metric 108

3.8.1 Rank metric correcting codes 109

3.8.2 Code by rank metric: a robust watermarking method for image cropping 113

3.9 Conclusion 121

3.10 References 121

Chapter 4 Invisibility 129
Pascal LEFEVRE, Philippe CARRE and David ALLEYSSON

4.1 Introduction 129

4.2 Color watermar