Forensic Authentication of Smartphone Screenshots Based on Metadata Tracing

Currently, smartphone screenshot images, as a swift and convenient tool for capturing and sharing information, have found widespread applications in daily life and professional work. However, simultaneously, the associated security and privacy concerns regarding these images have become increasingly salient. Due to the significant differences in their generation mechanisms between smartphone screenshots and captured images, this fact poses challenges for screenshot image traceability and forensics. In the current research and practical applications, technical research on tracing the sources of screenshot images remains in its nascent stage, with accurate tracing and identifying the source devices of specific images emerging as a pivotal research topic in the field of digital image forensics. This study focuses on developing a recognition methodology and system based on metadata features. By collecting screenshot samples from 52 smartphones of prevalent mobile phone brands in the market, metadata is extracted from the sample images, and a metadata feature database is subsequently established. The source device of the image is matched and identified by comparing multi-dimensional features, including model, device manufacturer, profile creator, rotation angle, file type, image width, and image height. Experimental results demonstrate that the proposed method exhibits high accuracy and reliability in identifying the origins of images for traceability purposes, thereby offering a novel technical approach for the field of digital forensics.