Slides

More documents

Recommendations

Info

4Now that we have the theory behind, the practical algorithms, and the test data, everything should be fine? Attacks against digital image forensics
Introducing attacks ✔ existing forensic schemes seem to work well under laboratory conditions ✔ usage in practical applications is documented ✘ What if there was a smart counterfeiter, who knew about our techniques? ◮ attacks: methods to systematically mislead digital image forensics Goals of an attacker ◮ hide traces of image manipulations Benefits of studying attacks ◮ eventually better detectors ◮ erase evidence about the source of an image ◮ pretend another source device of an image ◮ protect the source of an image (e .g. retain anonymity) Gloe & Kirchner Digital Image Forensics slide 52
Page 1 and 2:
I know what you have done in your l
Page 3 and 4:
This is actually not from a horror
Page 5 and 6:
This is actually not from a horror
Page 7 and 8:
. . . yet it is as scary, at least.
Page 9 and 10:
. . . yet it is as scary, at least.
Page 11 and 12:
Authenticity of images in the digit
Page 13 and 14:
Digital image forensics: a first gl
Page 15 and 16:
Page 17 and 18:
Page 19 and 20:
Two introductory examples ◮ digit
Page 21 and 22:
Page 23 and 24:
Page 25 and 26:
1 After all, it’s all about bits
Page 27 and 28:
By the way, what is computer forens
Page 29 and 30:
By the way, what is computer forens
Page 31 and 32:
Digital forensics: proposed ontolog
Page 33 and 34:
WARNING! The following slides inten
Page 35 and 36:
Computer forensics = Image forensic
Page 37 and 38:
Computer forensics = Image forensic
Page 39 and 40:
Computer forensics: a closer look p
Page 41 and 42:
suspicious traces? Computer forensi
Page 43 and 44:
suspicious traces? Computer forensi
Page 45 and 46:
Image forensics: a closer look orig
Page 47 and 48:
Image forensics: a closer look orig
Page 49 and 50:
Sensors: a source of uncertainty
Page 51 and 52:
Sensors: a source of uncertainty
Page 53 and 54:
Models: yet another dimensionality
Page 55 and 56:
Models: yet another dimensionality
Page 57 and 58:
Fundamentals of digital image foren
Page 59 and 60:
Page 61 and 62:
Page 63 and 64:
Page 65 and 66:
Page 67 and 68:
Page 69 and 70:
Page 71 and 72:
Page 73 and 74:
Page 75 and 76:
Image source identification goal: d
Page 77 and 78:
Intra- and inter-model similarities
Page 79 and 80:
Camera model identification ◮ mos
Page 81 and 82:
Some results on camera model identi
Page 83 and 84:
Camera model identification: overal
Page 85 and 86:
Camera device identification ◮ mo
Page 87 and 88:
Camera device identification ◮ mo
Page 89 and 90:
A typical noise residual Wavelet de
Page 91 and 92:
correlation coefficient Was it your
Page 93 and 94: Image source identfication: Summary
Page 95 and 96: Need a break? Ooops. . . submission
Page 97 and 98: Image manipulation detection Digita
Page 103 and 104: Resampling detection ◮ image mani
Page 105 and 106: Resampling detection scheme example
Page 107 and 108: Resampling detection scheme ωt ′
Page 109 and 110: Resampling detection scheme ωt ′
Page 111 and 112: It’s not only the biggest potato
Page 113 and 114: Color filter array interpolation
Page 115 and 116: Example application of CFA artifact
Page 117 and 118: Example application of CFA artifact
Page 119 and 120: Double JPEG compression Main idea /
Page 121 and 122: Double JPEG compression artifacts Q
Page 123 and 124: Church of our Ladies, Dresden A typ
Page 125 and 126: . . . and a practical application J
Page 127 and 128: 3Digital image forensics requires i
Page 129 and 130: How does your algorithm know that t
Page 131 and 132: How to capture 14 000 images . . .
Page 133: min / max temperature [ ◦ C] 8 4
Page 136 and 137: DOCMA Award Background ◮ creating
Page 138 and 139: DOCMA Award: some examples Original
Page 146 and 147: Digital forensics: proposed ontolog
Page 148 and 149: Counter-forensics: computer forensi
Page 154 and 155: Counter-forensics: image forensics
Page 156 and 157: Attacks: practical considerations W
Page 158 and 159: fin Concluding remarks
Page 160 and 161: Multimedia forensics: a growing fie
Page 162 and 163: A broader view 2 2 7 7 ICSI 2010 2A
Page 164 and 165: Computer forensics in a broader sen
Page 166 and 167: Computer forensics in a broader sen
Page 168: Image sources ⊲ Photoshop logo (t
show all

Slides

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?