PRNU Based Source Camera Identification for Webcam and Smartphone Videos

TL;DR

This paper explores using PRNU sensor noise patterns to identify the source camera in webcam and smartphone videos, extending existing image forensics techniques to video analysis.

Contribution

It introduces and evaluates three methods for source camera identification in videos, focusing on webcam and smartphone devices, which are less studied than still images.

Findings

PRNU-based methods can effectively identify camera sources in videos

Three different SCI methods are assessed for accuracy and robustness

Webcam and smartphone videos can be reliably linked to their source cameras

Abstract

This communication is about an application of image forensics where we use camera sensor fingerprints to identify source camera (SCI: Source Camera Identification) in webcam/smartphone videos. Sensor or camera fingerprints are based on computing the intrinsic noise that is always present in this kind of sensors due to manufacturing imperfections. This is an unavoidable characteristic that links each sensor with its noise pattern. PRNU (Photo Response Non-Uniformity) has become the default technique to compute a camera fingerprint. There are many applications nowadays dealing with PRNU patterns for camera identification using still images. In this work we focus on video, first on webcam video and afterwards on smartphone video. Webcams and smartphones are the most used video cameras nowadays. Three possible methods for SCI are implemented and assessed in this work.