Please use this identifier to cite or link to this item: http://hdl.handle.net/11452/26961
Title: Adaptive photo-response non-uniformity noise removal against image source attribution
Authors: Uludağ Üniversitesi/Mühendislik Fakültesi/Elektrik ve Elektronik Mühendisliği Bölümü.
0000-0002-3175-6041
0000-0002-6200-1717
0000-0002-3175-6041
Karaküçük, Ahmet
Dirik, Ahmet Emir
A-1996-2017
K-6977-2012
AAD-9762-2019
56008029100
23033658100
Keywords: Anonymization
Counter forensics
Privacy
PRNU
Sensor noise
Source camera attribution
Digital camera identification
Sensor
Origin
Computer science
Benchmarking
Cameras
Data privacy
Anonymization
Counter-Forensics
PRNU
Sensor noise
Source camera attribution
Image denoising
Issue Date: Mar-2015
Publisher: Elsevier
Citation: Karaküçük, A. ve Dirik A. E. (2015). "Adaptive photo-response non-uniformity noise removal against image source attribution". Digital Investigation, 12, 66-76.
Abstract: The main objective of image source anonymization is to protect the identity of the photographer against any attempts to identify the source camera device through PRNU noise analysis. One way of impeding image source attribution is to suppress the PRNU noise as much as possible. In this paper, we introduce an improvement on the existing adaptive photo-response non-uniformity (PRNU) denoising method against source camera identification. We evaluate the performance of the proposed method with substantial experimental analysis. We also provide anonymization benchmarks with other source anonymization techniques. The benchmarks' results show that the proposed method outperforms the adaptive PRNU denoising methods for various cameras including compact and smartphone in terms of speed and image quality. The experimental analysis also shows that it is possible to impede source camera identification by PRNU noise suppression even under extreme attack conditions.
URI: https://doi.org/10.1016/j.diin.2015.01.017
https://www.sciencedirect.com/science/article/pii/S1742287615000183
http://hdl.handle.net/11452/26961
ISSN: 1742-2876
Appears in Collections:Scopus
Web of Science

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