  During the investigation of criminal activity when evidence is available, the
issue at hand is determining the credibility of the video and ascertaining that
the video is real. Today, one way to authenticate the footage is to identify
the camera that was used to capture the image or video in question. While a
very common way to do this is by using image meta-data, this data can easily be
falsified by changing the video content or even splicing together content from
two different cameras. Given the multitude of solutions proposed to this
problem, it is yet to be sufficiently solved. The aim of our project is to
build an algorithm that identifies which camera was used to capture an image
using traces of information left intrinsically in the image, using filters,
followed by a deep neural network on these filters. Solving this problem would
have a big impact on the verification of evidence used in criminal and civil
trials and even news reporting.
