The Need for Steganalysis in Image Distribution Channels

Authors

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

DOI:

https://doi.org/10.13052/2245-1439.834

Keywords:

steganography, steganalysis

Abstract

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.

References

Mo Chen, Vahid Sedighi, Mehdi Boroumand, and Jessica Fridrich. Jpeg-phase-aware convolutional neural network for steganalysis of jpeg images. In Proceedings of the 5th ACM Workshop on Information Hiding and Multimedia Security, pages 75–84. ACM, 2017.

Rémi Cogranne, Vahid Sedighi, and Jessica Fridrich. Practical strategies for content-adaptive batch steganography and pooled steganalysis. In Acoustics, Speech and Signal Processing (ICASSP), 2017 IEEE International Conference on, pages 2122–2126. IEEE, 2017.

Ron Crandall. Some notes on steganography. In Posted on Steganogra- phy Mailing List, online: http://dde.binghamton.edu/download/Crandall matrix.pdf, (accessed Feb. 2018).

Andre Ester. Steganalysis of communication channels in social networks. Master’s thesis, TU Darmstadt, Germany, 2018.

Jessica J. Fridrich, Miroslav Goljan, and Dorin Hogea. Steganalysis of JPEG Images: Breaking the F5 Algorithm. Springer-Verlag, London, UK, online: http://www.ws.binghamton.edu/fridrich/Research/f5.pdf, (accessed Oct. 2017).

Tom Kellen. Hiding in Plain View: Could Steganography be a Terrorist Tool? SANS Institute, online: https://www.sans.org/reading-room/whitepapers/stenganography/hiding-plain-view-steganography-terrorist-tool-551, (accessed Sept. 2017).

Andrew D Ker. Batch steganography and pooled steganalysis. In International Workshop on Information Hiding, pages 265–281. Springer, 2006.

Li Lin, Jennifer Newman, Stephanie Reinders, Yong Guan, and Min Wu. Domain adaptation in steganalysis for the spatial domain. Electronic Imaging, 2018(7), 2018.

Declan McCullagh. Bin Laden: Steganography Master? Wired Magazine, online: https://www.wired.com/2001/02/bin-laden-steganography-master, (accessed Sept. 2017).

Noah Shachtman. FBI: Spies HID Secret Messages on Public Websites. Wired Magazine, online: https://www.wired.com/2010/06/alleged-spies-hid-secret-messages-on-public-websites, (accessed Sept. 2017).

Martin Steinebach, Andre Ester, and Huajian Liu. Channel steganalysis. In Proceedings of the 13th International Conference on Availability, Reliability and Security, ARES 2018, pages 9:1–9:8, New York, NY, USA, 2018. ACM.

Martin Steinebach, Andre Ester, Huajian Liu, and Sascha Zmudzinski. Double embedding steganalysis: Steganalysis with low false positive rates. In MPS ’18: Proceedings of the 2nd International Workshop on Multimedia Privacy and Security, CCS 2018, New York, NY, USA, 2018. ACM.

Clement Fuji Tsang and Jessica Fridrich. Steganalyzing images of arbitrary size with cnns. Electronic Imaging, 2018(7), 2018.

Andreas Westfeld. F5 – a steganographic algorithm. In Moskowitz I.S. (eds) Information Hiding. IH 2001. Lecture Notes in Computer Science, volume 2137, pages 289–302. Springer-Verlag, London, UK.

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Published

2018-12-14

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Articles