Event / Presentation Title

Source Anonymization of Digital Images: A Counter–Forensic Attack on PRNU based Source Identification Techniques

Proposal / Submission Type

Peer Reviewed Paper

Abstract

A lot of photographers and human rights advocates need to hide their identity while sharing their images on the internet. Hence, source–anonymization of digital images has become a critical issue in the present digital age. The current literature contains a number of digital forensic techniques for “source–identification” of digital images, one of the most efficient of them being Photo–Response Non–Uniformity (PRNU) sensor noise pattern based source detection. PRNU noise pattern being unique to every digital camera, such techniques prove to be highly robust way of source–identification. In this paper, we propose a counter–forensic technique to mislead this PRNU sensor noise pattern based source–identification, by using a median filter to suppress PRNU noise in an image, iteratively. Our experimental results prove that the proposed method achieves considerably higher degree of source anonymity, measured as an inverse of Peak–to–Correlation Energy (PCE) ratio, as compared to the state–of–the–art.

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Source Anonymization of Digital Images: A Counter–Forensic Attack on PRNU based Source Identification Techniques

A lot of photographers and human rights advocates need to hide their identity while sharing their images on the internet. Hence, source–anonymization of digital images has become a critical issue in the present digital age. The current literature contains a number of digital forensic techniques for “source–identification” of digital images, one of the most efficient of them being Photo–Response Non–Uniformity (PRNU) sensor noise pattern based source detection. PRNU noise pattern being unique to every digital camera, such techniques prove to be highly robust way of source–identification. In this paper, we propose a counter–forensic technique to mislead this PRNU sensor noise pattern based source–identification, by using a median filter to suppress PRNU noise in an image, iteratively. Our experimental results prove that the proposed method achieves considerably higher degree of source anonymity, measured as an inverse of Peak–to–Correlation Energy (PCE) ratio, as compared to the state–of–the–art.