RAISE

TLDR

Digital forensics seeks to authenticate media, but the proliferation of multimedia and advanced graphics tools makes forging images easy, creating a need for reliable validation tools. RAISE is a large, 8,156‑image raw‑image dataset with annotations and metadata designed to serve as a benchmark for forensic researchers. The dataset was collected and organized with accompanying metadata, and a recent JPEG‑compression‑detection method was evaluated on it. Testing a recent JPEG‑compression‑detection method on RAISE shows the dataset’s suitability for evaluating forensic algorithms.

Abstract

Digital forensics is a relatively new research area which aims at authenticating digital media by detecting possible digital forgeries. Indeed, the ever increasing availability of multimedia data on the web, coupled with the great advances reached by computer graphical tools, makes the modification of an image and the creation of visually compelling forgeries an easy task for any user. This in turns creates the need of reliable tools to validate the trustworthiness of the represented information. In such a context, we present here RAISE, a large dataset of 8156 high-resolution raw images, depicting various subjects and scenarios, properly annotated and available together with accompanying metadata. Such a wide collection of untouched and diverse data is intended to become a powerful resource for, but not limited to, forensic researchers by providing a common benchmark for a fair comparison, testing and evaluation of existing and next generation forensic algorithms. In this paper we describe how RAISE has been collected and organized, discuss how digital image forensics and many other multimedia research areas may benefit of this new publicly available benchmark dataset and test a very recent forensic technique for JPEG compression detection.