Dafale, Ninad N. (2017) Source Anonymization Through Counter Forensics. MTech thesis.
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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 art and science of impeding and misleading forensic analysis of the digital image is known as Counter Forensics. 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 a highly robust way of source–identification. In this work, first, we propose a counter–forensic technique to mislead this PRNU sensor noise pattern based source–identification, by using a median filter and Modified hybrid median filter to suppress PRNU noise in an image, iteratively. Our experimental results prove that the proposed methods achieve a 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.
Next, we deliver an attack on digital images, where we completely remove the traces of sensor pattern noises of their source devices, so as to deceive forensic investigations and again, we substitute the sensor pattern of a given image with that of a different (wrong) source device, such that it now appears to the forensic analyst, that the image was produced by device B, whereas originally it was produced by A. Our experimental results prove that high correlation is achieved between a tampered image and a wrong device, suggesting considerably high degree of anonymity, hence misleading forensics investigation.
|Item Type:||Thesis (MTech)|
|Uncontrolled Keywords:||Counter Forensics; Digital Forensics; Median Filter; Modified hybrid median filter (MHMF); Photo Response Non-Uniformity; Sensor pattern noise; Winer filter; Wavelet filter|
|Subjects:||Engineering and Technology > Computer and Information Science > Image Processing|
|Divisions:||Engineering and Technology > Department of Computer Science|
|Deposited By:||Mr. Kshirod Das|
|Deposited On:||03 May 2018 12:17|
|Last Modified:||03 May 2018 12:17|
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