Cover-aware Steganalysis

Authors

  • Niklas Bunzel Fraunhofer Institute for Secure Information Technology SIT, Darmstadt, Germany
  • Martin Steinebach Fraunhofer Institute for Secure Information Technology SIT, Darmstadt, Germany https://orcid.org/0000-0002-0240-0388
  • Huajian Liu Fraunhofer Institute for Secure Information Technology SIT, Darmstadt, Germany https://orcid.org/0000-0003-3470-0999

DOI:

https://doi.org/10.13052/jcsm2245-1439.1011

Keywords:

Steganography, Steganalysis, Information Hiding

Abstract

The increasing digitization offers new ways, possibilities and needs for a secure transmission of information. Steganography and its analysis constitute an essential part of IT-Security. In this work we show how methods of blind-steganalysis can be improved to work in cover-aware scenarios, we will call this non-blind steganalysis. The main objective was to examine how to take advantage of the knowledge of reference images to maximize the accuracy-rate of the analysis.


Therefore we evaluated common stego-tools and their embedding algorithms and established a dataset of 353110 images. The images have been applied to test the potency of the improved methods of the non-blind steganalysis. The results show that the accuray can be significantly improved by using cover-images to produce reference images. Also the aggregation of the outcomes has shown to have a positive impact on the accuracy. Particularly noteworthy is the correlation between the qualities of the stego- and coverimages. Only by consindering both, the accuracy could strongly be improved. Interestingly the difference between both qualities also has a deep impact on the results.

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Author Biographies

Niklas Bunzel, Fraunhofer Institute for Secure Information Technology SIT, Darmstadt, Germany

Niklas Bunzel received his B.Sc. and M.Sc. degrees in computer science and IT security from Technical University Darmstadt 2015 and 2020, respectively. He is currently a research scientist at Fraunhofer Institute for Secure Information Technology (SIT). His major research interests include artificial intelligence, IT security and steganography.

Martin Steinebach, Fraunhofer Institute for Secure Information Technology SIT, Darmstadt, Germany

Martin Steinebach is the manager of the Media Security and IT Forensics division at Fraunhofer SIT. From 2003 to 2007 he was the manager of the Media Security in IT division at Fraunhofer IPSI. He studied computer science at the Technical University of Darmstadt and finished his diploma thesis on copyright protection for digital audio in 1999. In 2003 he received his PhD at the Technical University of Darmstadt for this work on digital audio watermarking. In 2016 he became honorary professor at the TU Darmstadt. He gives lectures on Multimedia Security as well as Civil Security. He is Principle Investigator at ATHENE and represents IT Forensics and AI Security. Before he was Principle Investigator at CASED with the topics Multimedia Security and IT Forensics. In 2012 his work on robust image hashing for detection of child pornography reached the second rank Deutscher IT Sicherheitspreis”, an award funded by Host Görtz.

Huajian Liu, Fraunhofer Institute for Secure Information Technology SIT, Darmstadt, Germany

Huajian Liu received his B.S. and M.S. degrees in electronic engineering from Dalian University of Technology, China, in 1999 and 2002, respectively, and his Ph.D. degree in computer science from Technical University Darmstadt, Germany, in 2008. He is currently a senior research scientist at Fraunhofer Institute for Secure Information Technology (SIT). His major research interests include information security, digital watermarking, robust hashing and digital forensics.

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Published

2021-03-20

Issue

Section

ARES 2020 Workshops