Anti-forensic Approach to Remove Stego Content from Images and Videos

Authors

  • P. P. Amritha TIFAC-CORE in Cyber Security, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India
  • M. Sethumadhavan TIFAC-CORE in Cyber Security, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India
  • R. Krishnan TIFAC-CORE in Cyber Security, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India
  • Saibal Kumar Pal Scientific Analysis Group, DRDO, Delhi, India

DOI:

https://doi.org/10.13052/2245-1439.831

Keywords:

Steganography, Steganalysis, Image processing, Variational deconvolution, Markov features

Abstract

Covert transmission of information hidden in different media to either a general or targeted audience constitutes steganography. However, this technique can be misused to transmit undesirable information. Traditionally the removal of such content necessitated the knowledge of the steganographic algorithm used. However,we address the scenario where such stego is removed using generic image processing operations along with an anti forensic method without assuming any knowledge of the steganographic algorithm used. The application of generic image processing operations also causes degradation of cover image, which can also be restored using this anti forensic method. Our procedure has been tested on a variety of steganographic algorithms including HUGO-BD,WOW, Synch and J-UNIWARD. By applying universal steganalysis we found that all images which have been subjected to our procedure have become stego free. However, a direct evaluation of the stego content assuming knowledge of the stego content and its location showed that 80 percentage of the stego is removed without significantly impacting the visual image quality. Video stream containing isolated static images have been addressed in this paper. The peak signal-to-noise ratio and structural similarity metric values of cleaned images and videos are found to be in the range 30dB–40dB and 0.81–0.99 respectively.

 

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Author Biographies

P. P. Amritha, TIFAC-CORE in Cyber Security, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India

P. P. Amritha received her M.Tech. (Cyber Security) from Amrita Vishwa Vidyapeetham, currently pursuing her PhD at Amrita Vishwa Vidyapeetham. Her current research interests include: Steganography and code obfuscation.

M. Sethumadhavan, TIFAC-CORE in Cyber Security, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India

M. Sethumadhavan received his PhD (Number Theory) from Calicut Regional Engineering College. Currently, he is working as a Professor in the Centre for Cyber Security, Amrita Vishwa Vidyapeetham, Coimbatore. His current research interests include: Cryptography and Boolean functions.

R. Krishnan, TIFAC-CORE in Cyber Security, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India

R. Krishnan received his PhD from IISc, Bangalore. He is currently an Adjunct Professor at Amrita Vishwa Vidyapeetham, Coimbatore. His current research interests include: Image processing and remote sensing.

Saibal Kumar Pal, Scientific Analysis Group, DRDO, Delhi, India

Saibal Kumar Pal is presently the Director, Information Technology & Cyber Security at Defence Research & Development Organization (DRDO), New Delhi. His areas of interest are Cyber Security, Cryptography, and Computational Intelligence & High-Performance Computing. He has contributed in a number of R&D projects and international collaborations.

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Published

2018-04-07

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