Source Camera Identification and Detection in Digital Videos through
  Blind Forensics
Venkata Udaya Sameer Shilpa Mukhopadhyay Ruchira Naskar Ishaan Dali
Source camera identification in digital videos is the problem of associating
an unknown digital video with its source device, within a closed set of
possible devices. The existing techniques in source detection of digital videos
try to find a fingerprint of the actual source in the video in form of PRNU
(Photo Response Non--Uniformity), and match it against the SPN (Sensor Pattern
Noise) of each possible device. The highest correlation indicates the correct
source. We investigate the problem of identifying a video source through a
feature based approach using machine learning. In this paper, we present a
blind forensic technique of video source authentication and identification,
based on feature extraction, feature selection and subsequent source
classification. The main aim is to determine whether a claimed source for a
video is actually its original source. If not, we identify its original source.
Our experimental results prove the efficiency of the proposed method compared
to traditional fingerprint based technique.