The Need for Steganalysis in Image Distribution Channels


  • Martin Steinebach Fraunhofer SIT, Darmstadt, Germany
  • Huajian Liu Fraunhofer SIT, Darmstadt, Germany
  • Andre Ester Fraunhofer SIT, Darmstadt, Germany



steganography, steganalysis


The rise of social networks during the last 10 years has created a situation in which up to 100 million new images and photographs are uploaded and shared by users every day. This environment poses an ideal background for those who wish to communicate covertly by the use of steganography. It also creates a new set of challenges for steganalysts, who have to shift their field of work away from a purely scientific laboratory environment and into a diverse real-world scenario, while at the same time having to deal with entirely new problems, such as the detection of steganographic channels or the impact that even a low false positive rate has when investigating the millions of images which are shared every day on social networks. We evaluate how to address these challenges with traditional steganographic and statistical methods, rather than using high performance computing and machine learning. To achieve this we first analyze the steganographic algorithm F5 applied to images with a high degree of diversity, as would be seen in a typical social network.We show that the biggest challenge lies in the detection of images whose payload is less then 50% of the available capacity of an image.We suggest new detection methods and apply these to the problem of channel detection in social network. We are able to show that using our attacks we are able to detect the majority of covert F5 channels after a mix containing 10 stego images has been classified by our scheme.



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Author Biographies

Martin Steinebach, Fraunhofer 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 CRISP and represents IT Forensics and Big Data 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 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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