Campus Units

Electrical and Computer Engineering, Mathematics, Center for Statistics and Applications in Forensic Evidence (CSAFE)"

Document Type

Article

Publication Version

Published Version

Publication Date

2019

Journal or Book Title

Electronic Imaging

Volume

536

First Page

1

Last Page

11

DOI

10.2352/ISSN.2470-1173.2019.5.MWSF-536

Abstract

In this paper, we present a new reference dataset simulating digital evidence for image (photographic) steganography. Steganography detection is a digital image forensic topic that is relatively unknown in practical forensics, although stego app use in the wild is on the rise. This paper introduces the first database consisting of mobile phone photographs and stego images produced from mobile stego apps, including a rich set of side information, offering simulated digital evidence. StegoAppDB, a steganography apps forensics image database, contains over 810,000 innocent and stego images using a minimum of 10 different phone models from 24 distinct devices, with detailed provenanced data comprising a wide range of ISO and exposure settings, EXIF data, message information, embedding rates, etc. We develop a camera app, Cameraw, specifically for data acquisition, with multiple images per scene, saving simultaneously in both DNG and high-quality JPEG formats. Stego images are created from these original images using selected mobile stego apps through a careful process of reverse engineering. StegoAppDB contains cover-stego image pairs including for apps that resize the stego dimensions. We retain the original devices and continue to enlarge the database, and encourage the image forensics community to use StegoAppDB. While designed for steganography, we discuss uses of this publicly available database to other digital image forensic topics.

Comments

This is an article published as Newman, Jennifer, Li Lin, Wenhao Chen, Stephanie Reinders, Yangxiao Wang, Min Wu, and Yong Guan. "StegoAppDB: a Steganography Apps Forensics Image Database." Electronic Imaging 2019, no. 5 (2019): 536-1. Posted with permission of CSAFE.

Copyright Owner

Society for Imaging Science and Technology

Language

en

File Format

application/pdf

Share

COinS