digital camera identification · 2018. 11. 30. · paper results • setting far to 10-3 gives frr...
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Digital Camera Identification
Neil Jenkins
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The Problem
?
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The Digital Image Pathway
Light
Magic
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Noise
• Shot noise
• Pattern noise
- Fixed pattern noise
- Photo-response non-uniformity noise (PRNU)
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Modelling theSensor Output
yij = fij(xij + ηij) + cij + εij
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The Algorithm
1. Calculate the camera reference patterns
2. Look for correlation between the image and the different patterns
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Calculating the Reference Pattern
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Calculating the Reference Pattern
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Looking for Correlation
?
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Looking for Correlation
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Looking for Correlation
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Looking for Correlation
Original Image Filtered Image
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Looking for correlation
Original Image Filtered Image
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Looking for Correlation
Original Image Filtered Image
-
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Looking for Correlation
Noise Residual
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Looking for Correlation
corr(n, r) =(n− n) · (r− r)�n− n��r− r�
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Experiment
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Experiment
100x
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Experiment
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Experiment
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Results
-0.02 0 0.02 0.04 0.05 0.07
Webcam Images Other Images
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Paper results
• Setting FAR to 10-3 gives FRR of 4.68x10-3 in worst case and down to 1.14x10-11
• Gamma correction of images barely affects reliability
• JPEG also irrelevant unless high compression
• Stable over time
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Algorithm Mark II
• More detailed mathematical model of how light is captured by sensor
I = gγ · [(1 + K)Y + Λ + Θs + Θr]γ + Θq
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Algorithm Mark II
• Determine PRNU using a maximum likelihood estimator
• Detection is binary hypothesis testing
• Correlation Predictor
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Large scale test
• Apply algorithm to 1,000,000+ images
• Extensive test of reliability
• False rejection rate < 0.024 when threshold such that false acceptance < 2.4
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Questions