New Approaches Based on PRNU-CNN for Image Camera Source Attribution in Forensic Investigations

Digital image forensics currently mainly uses PRNU noise as a fingerprint to attribute an image to a particular camera. However PRNU is usually extracted manually using Maximum Likelihood estimation from multiple images from the same source device. In this paper we show that the PRNU can be learned in a data driven fashion using a ResNet based neural network. We also show that it is possible to train a neural network for camera attribution directly on the residual noise, that contains both the PRNU and a random component. We show that both approaches are valid as we obtained results comparable with the state of the art. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).