  Patch-Match is an efficient algorithm used for structural image editing and
available as a tool on popular commercial photo-editing software. The tool
allows users to insert or remove objects from photos using information from
similar scene content. Recently, a modified version of this algorithm was
proposed as a counter-measure against Photo-Response Non-Uniformity (PRNU)
based Source Camera Identification (SCI). The algorithm can provide anonymity
at a great rate (97\%) and impede PRNU based SCI without the need of any other
information, hence leaving no-known recourse for the PRNU-based SCI. In this
paper, we propose a method to identify sources of the Patch-Match-applied
images by using randomized subsets of images and the traditional PRNU based SCI
methods. We evaluate the proposed method on two forensics scenarios in which an
adversary makes use of the Patch-Match algorithm and distorts the PRNU noise
pattern in the incriminating images he took with his camera. Our results show
that it is possible to link sets of Patch-Match-applied images back to their
source camera even in the presence of images that come from unknown cameras. To
our best knowledge, the proposed method represents the very first
counter-measure against the usage of of Patch-Match in the digital forensics
literature.
