Adversary-aware, data-driven detection of double JPEG compression: How to make counter-forensics harder

@article{Barni2016AdversaryawareDD,
  title={Adversary-aware, data-driven detection of double JPEG compression: How to make counter-forensics harder},
  author={Mauro Barni and Zhipeng Chen and Benedetta Tondi},
  journal={2016 IEEE International Workshop on Information Forensics and Security (WIFS)},
  year={2016},
  pages={1-6}
}
In the attempt to investigate the final race of arms between the forensic analyst and the adversary in practical scenarios based on data-driven approaches, we introduce the idea of adversary-aware SVM-based forensic detection. By focusing on the problem of double JPEG compression, we first propose an improved universal counter-forensic (C-F) attack which works against any forensic detector based on the first order statistics of block-DCT coefficients and show its good performance against three… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-10 OF 10 CITATIONS

An improved anti-forensic technique for JPEG compression

  • Multimedia Tools and Applications
  • 2019
VIEW 11 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Digital Communication. Towards a Smart and Secure Future Internet

  • Communications in Computer and Information Science
  • 2017
VIEW 12 EXCERPTS
CITES BACKGROUND
HIGHLY INFLUENCED

Higher-order, adversary-aware, double JPEG-detection via selected training on attacked samples

  • 2017 25th European Signal Processing Conference (EUSIPCO)
  • 2017
VIEW 5 EXCERPTS
CITES BACKGROUND & METHODS

Adversarial Multimedia Forensics: Overview and Challenges Ahead

  • 2018 26th European Signal Processing Conference (EUSIPCO)
  • 2018
VIEW 3 EXCERPTS
CITES METHODS & BACKGROUND

Mislgan: An Anti-Forensic Camera Model Falsification Framework Using A Generative Adversarial Network

  • 2018 25th IEEE International Conference on Image Processing (ICIP)
  • 2018
VIEW 1 EXCERPT
CITES BACKGROUND

Secure Detection of Image Manipulation by Means of Random Feature Selection

  • IEEE Transactions on Information Forensics and Security
  • 2018
VIEW 1 EXCERPT
CITES BACKGROUND

Detecting anti-forensic attacks on demosaicing-based camera model identification

  • 2017 IEEE International Conference on Image Processing (ICIP)
  • 2017
VIEW 1 EXCERPT
CITES BACKGROUND

References

Publications referenced by this paper.
SHOWING 1-10 OF 23 REFERENCES

The Earth Mover's Distance as a Metric for Image Retrieval

  • International Journal of Computer Vision
  • 2000
VIEW 3 EXCERPTS
HIGHLY INFLUENTIAL

Anti-Forensics and Countermeasures of Electrical Network Frequency Analysis

  • IEEE Transactions on Information Forensics and Security
  • 2013
VIEW 1 EXCERPT