
Conference/Workshop:
IEEE Asia-Pacific Signal and Information Processing Association, 2018, Annual Summit and Conference (APSIPA ASC)
Journal: Proceedings, APSIPA Annual Summit and Conference 2018
Published: 2018
Primary Author: Wenhao Chen
Secondary Authors: L. Lin, M. Wu, Y. Guan, J. Newman
Type: Publication
Research Area: Digital
Digital image forensics is a young but maturing field, encompassing key areas such as camera identification, detection of forged images, and steganalysis. However, large gaps exist between academic results and applications used by practicing forensic analysts. To move academic discoveries closer to real-world implementations, it is important to use data that represent “in the wild” scenarios. For detection of stego images created from steganography apps, images generated from those apps are ideal to use. In this paper, we present our work to perform steg detection on images from mobile apps using two different approaches: “signature” detection, and machine learning methods. A principal challenge of the ML task is to create a great many of stego images from different apps with certain embedding rates. One of our main contributions is a procedure for generating a large image database by using Android emulators and reverse engineering techniques, the first time ever done. We develop algorithms and tools for signature detection on stego apps, and provide solutions to issues encountered when creating ML classifiers.
Related Resources


Forensic Footwear: A Retrospective of the Development of the MANTIS Shoe Scanning System
July 10, 2025
There currently are no shoe-scanning devices developed in the United States that can operate in a real-world, variable-weather environment in …

Examiner consistency in perceptions of fingerprint minutia rarity
July 10, 2025
Friction ridge examiners (FREs) identify distinctive features (minutiae) in fingerprints and consider how rare these observed minutiae are in their …