PRNU-based Image Classification of Origin Social Network with CNN

Roberto Caldelli, Irene Amerini, Chang Tsun Li
2018 2018 26th European Signal Processing Conference (EUSIPCO)  
A huge amount of images are continuously shared on social networks (SNs) daily and, in most of cases, it is very difficult to reliably establish the SN of provenance of an image when it is recovered from a hard disk, a SD card or a smartphone memory. During an investigation, it could be crucial to be able to distinguish images coming directly from a photo-camera with respect to those downloaded from a social network and possibly, in this last circumstance, determining which is the SN among a
more » ... ined group. It is well known that each SN leaves peculiar traces on each content during the upload-download process; such traces can be exploited to make image classification. In this work, the idea is to use the PRNU, embedded in every acquired images, as the "carrier" of the particular SN traces which diversely modulate the PRNU. We demonstrate, in this paper, that SNmodulated noise residual can be adopted as a feature to detect the social network of origin by means of a trained convolutional neural network (CNN).
doi:10.23919/eusipco.2018.8553160 dblp:conf/eusipco/CaldelliAL18 fatcat:kjbxfvttyjc5dc5jhydfz65iue