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IFIP International Conference on Communications and Multimedia Security

CMS 2012: Communications and Multimedia Security pp 3–15Cite as

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Robust Resampling Detection in Digital Images

Robust Resampling Detection in Digital Images

  • Hieu Cuong Nguyen18 &
  • Stefan Katzenbeisser18 
  • Conference paper
  • 1201 Accesses

  • 8 Citations

Part of the Lecture Notes in Computer Science book series (LNSC,volume 7394)

Abstract

To create convincing forged images, manipulated images or parts of them are usually exposed to some geometric operations which require a resampling step. Therefore, detecting traces of resampling became an important approach in the field of image forensics. In this paper, we revisit existing techniques for resampling detection and design some targeted attacks in order to assess their reliability. We show that the combination of multiple resampling and hybrid median filtering works well for hiding traces of resampling. Moreover, we propose an improved technique for detecting resampling using image forensic tools. Experimental evaluations show that the proposed technique is good for resampling detection and more robust against some targeted attacks.

Keywords

  • Digital image forensics
  • resampling detection
  • targeted attack

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Author information

Authors and Affiliations

  1. Computer Science Department, Darmstadt University of Technology, Germany

    Hieu Cuong Nguyen & Stefan Katzenbeisser

Authors
  1. Hieu Cuong Nguyen
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  2. Stefan Katzenbeisser
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Editor information

Editors and Affiliations

  1. Department of Computer Science, IBBT-DistriNet, K.U. Leuven, Celestijnenlaan 200A, 3001, Leuven, Belgium

    Bart De Decker

  2. School of Computing, University of Kent, CT2 7NZ, Canterbury, Kent, UK

    David W. Chadwick

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© 2012 IFIP International Federation for Information Processing

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Cite this paper

Nguyen, H.C., Katzenbeisser, S. (2012). Robust Resampling Detection in Digital Images. In: De Decker, B., Chadwick, D.W. (eds) Communications and Multimedia Security. CMS 2012. Lecture Notes in Computer Science, vol 7394. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32805-3_1

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  • DOI: https://doi.org/10.1007/978-3-642-32805-3_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32804-6

  • Online ISBN: 978-3-642-32805-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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