Forensic Scanner Identification Using Machine Learning
This addresses the need for forensic image analysis to combat image tampering, though it is incremental as it applies existing deep learning methods to scanner identification.
The paper tackles the problem of identifying the source scanner of digital images using a deep learning system, achieving high accuracy and generating reliability maps to indicate manipulated regions.
Due to the increasing availability and functionality of image editing tools, many forensic techniques such as digital image authentication, source identification and tamper detection are important for forensic image analysis. In this paper, we describe a machine learning based system to address the forensic analysis of scanner devices. The proposed system uses deep-learning to automatically learn the intrinsic features from various scanned images. Our experimental results show that high accuracy can be achieved for source scanner identification. The proposed system can also generate a reliability map that indicates the manipulated regions in an scanned image.