Warwick Image Forensics Dataset for Device Fingerprinting In Multimedia Forensics
This provides a new dataset for the digital forensic community to address challenges in device fingerprinting due to modern camera technologies, but it is incremental as it focuses on data collection rather than novel methods.
The authors tackled the challenge of device fingerprinting in multimedia forensics by creating the Warwick Image Forensics Dataset, which includes over 58,600 images from 14 digital cameras with varied exposure settings to support multi-frame computational photography algorithms.
Device fingerprints like sensor pattern noise (SPN) are widely used for provenance analysis and image authentication. Over the past few years, the rapid advancement in digital photography has greatly reshaped the pipeline of image capturing process on consumer-level mobile devices. The flexibility of camera parameter settings and the emergence of multi-frame photography algorithms, especially high dynamic range (HDR) imaging, bring new challenges to device fingerprinting. The subsequent study on these topics requires a new purposefully built image dataset. In this paper, we present the Warwick Image Forensics Dataset, an image dataset of more than 58,600 images captured using 14 digital cameras with various exposure settings. Special attention to the exposure settings allows the images to be adopted by different multi-frame computational photography algorithms and for subsequent device fingerprinting. The dataset is released as an open-source, free for use for the digital forensic community.