Skip to content

Tackling Android Stego Apps in the Wild

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
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

Statistical Methods for the Forensic Analysis of User-Event Data

Statistical Methods for the Forensic Analysis of User-Event Data

A common question in forensic analysis is whether two observed data sets originate from the same source or from different sources. Statistical approaches to addressing this question have been widely…
Statistical Methods for the Forensic Analysis of Geolocated Event Data

Statistical Methods for the Forensic Analysis of Geolocated Event Data

A common question in forensic analysis is whether two observed data sets originated from the same source or from different sources. Statistical approaches to addressing this question have been widely…
Statistical models to predict exposure settings using two different iPhone camera apps

Statistical models to predict exposure settings using two different iPhone camera apps

The StegoAppDB [Newman, J. (2019)] is a digital image database containing camera data from Android and iPhone mobile phones and developed for forensic purposes. Taken with a custom-designed camera app…
Statistical methods for digital image forensics: Algorithm mismatch for blind spatial steganalysis and score-based likelihood ratios for camera device identification

Statistical methods for digital image forensics: Algorithm mismatch for blind spatial steganalysis and score-based likelihood ratios for camera device identification

Forensic science currently faces a variety of challenges. Statistically suitable reference databases need to be developed and maintained. Subjective methods that can introduce bias need to be replaced by objective…