Matthew C. Stamm

Research

My research seeks to provide information verification and security in scenarios when an information source cannot be trusted.

The majority of my research is in digital multimedia forensics. Digital multimedia forensics involves the developing mathematical techniques to identify multimedia forgeries such as falsified images and videos. This research is particularly important because widely available editing software enables multimedia forgers to create perceptually realistic forgeries.

I also perform research on anti-forensic operations designed to fool forensic techniques. By studying anti-forensics, researchers can identify and address weaknesses in existing forensic techniques as well as develop techniques capable of identifying the use of anti-forensics.

A link to my Google Scholar profile containing all of my publications and their citations can be found here.

Journal Publications

  1. T. Huang, N. Kandasamy, H. Sethu, and M. C. Stamm, "An efficient strategy for online performance monitoring of datacenters via adaptive sampling," Accepted for Publication in IEEE Transactions on Cloud Computing, 2016.
  2. X. Chu, Y. Chen, M. C. Stamm, and K. J. R. Liu, "Information theoretical limit of operation forensics: The forensicability," IEEE Transactions on Information Forensics and Security, vol. 11, no. 4, pp. 774-788, April 2016.
  3. X. Chu, M. C. Stamm, and K. J. R. Liu, "Compressive sensing forensics," IEEE Transactions on Information Forensics and Security, vol. 10, no. 7, pp. 1416-1431, Jul. 2015.
  4. X. Chu, M. C. Stamm, Y. Chen, and K. J. R. Liu, "On antiforensic concealability with rate- distortion tradeoff," IEEE Transactions on Image Processing, vol. 24, no. 3, pp. 1087-1100, Mar. 2015.
  5. X. Kang, M. C. Stamm, A. Peng, and K. J. R. Liu, "Robust median filtering forensics using an autoregressive model," IEEE Transactions on Information Forensics and Security, vol. 8, no. 9, pp. 1456_1468, Sep. 2013.
  6. M. C. Stamm, M. Wu, and K. J. R. Liu, "Information forensics: An overview of the first decade," IEEE Access, vol. 1, pp. 167-200, 2013.
  7. M. C. Stamm, W. S. Lin, and K. J. R. Liu, "Temporal Forensics and Anti-Forensics in Digital Videos", IEEE Trans. on Information Forensics and Security, vol. 7, no. 4, pp. 1315 - 1329, Aug. 2012.
  8. M. C. Stamm and K. J. R. Liu, "Anti-Forensics of Digital Image Compression", IEEE Transactions on Information Forensics and Security, vol. 6, no. 3, pp. 1050 - 1065, Sep. 2011.
  9. M. C. Stamm and K. J. R. Liu, "Forensic Detection of Image Manipulation Using Statistical Intrinsic Fingerprints", IEEE Transactions on Information Forensics and Security, vol. 5, no. 3, pp. 492 - 506, Sep. 2010.

Conference Publications

  1. X. Zhao and M. C. Stamm, "Computationally efficient demosaicing filter estimation for forensic camera model identification," IEEE International Conference on Image Processing (ICIP), Phoenix, AZ, Sep. 2016.
  2. B. Bayar and M. C. Stamm, "A Deep Learning Approach To Universal Image Manipulation Detection Using A New Convolutional Layer," ACM Workshop on Information Hiding and Multimedia Security, Vigo, Spain, Jun. 2016.
  3. S. DeCelles, T. Huang, M. C. Stamm, N. Kandasamy, "Detecting incipient faults in software systems: A compressed sampling-based approach," IEEE International Conference on Cloud Computing (CLOUD), (15% acceptance rate), San Francisco, CA, Jun. 2016.
  4. O. Mayer and M. C. Stamm, "Improved forgery detection with lateral chromatic aberration," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Shanghai, China, Mar. 2016.
  5. S. Decelles, M. C. Stamm, and N. Kandasamy, "Efficient online performance monitoring of computing systems using predictive models," IEEE/ACM International Conference on Utility & Cloud Computing (UCC) (27.5% acceptance rate), Limassol, Cyprus, Dec. 2015, pp. 152-161.
  6. C. Chen and M. C. Stamm, "Camera model identification framework using an ensemble of demosaicing features," IEEE International Workshop on Information Forensics and Security (WIFS), Rome, Italy, Nov. 2015, pp. 1-6.
  7. O. Mayer and M. C. Stamm, "Anti-forensics of chromatic aberration," Proc. IS&T SPIE Electronic Imaging, Media Watermarking, Security, and Forensics, San Francisco, CA, Feb. 2015, pp. 94 090M-94 090M.
  8. X. Chu, Y. Chen, M. C. Stamm, and K. J. R. Liu, "Information theoretical limit of compression forensics," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Florence, Italy, May 2014, pp. 2689-2693.
  9. M. C. Stamm, X. Chu, and K. J. R. Liu, "Forensically determining the order of signal processing operations," IEEE International Workshop on Information Forensics and Security (WIFS), Guangzhou, China, Nov. 2013, pp. 162-167.
  10. M. C. Stamm and and K. J. R. Liu, "Protection Against Reverse Engineering in Digital Cameras," IEEE International Conference on Acoustic, Speech, and Signal Processing (ICASSP), Vancouver, Canada, May 2013. [Invited for Special Session on Adversarial Signal Processing]
  11. X. Chu, M. C. Stamm, and and K. J. R. Liu, "Concealability-Rate-Distortion Tradeoff in Image Compression Anti-Forensics", IEEE International Conference on Acoustic, Speech, and Signal Processing (ICASSP), Vancouver, Canada, May 2013.
  12. Z.-H. Wu, M. C. Stamm, and and K. J. R. Liu, "Anti-Forensics of Median Filtering", IEEE International Conference on Acoustic, Speech, and Signal Processing (ICASSP), Vancouver, Canada, May 2013.
  13. X. Kang, M. C. Stamm, A. Peng, and K. J. R. Liu, "Robust Median Filtering Forensics Based on the Autoregressive Model of Median Filtered Residual", Proc. APSIPA Annual Summit and Conference, Hollywood, California, pp. 1-9, December 2012.
  14. X. Chu, M. C. Stamm, and K. J. R. Liu, "Forensic Identification of Compressive Sensing in Nearly Sparse Signals", IEEE Int. Conf. Image Processing (ICIP), Orlando, Florida, pp. 257-260, October 2012.
  15. M. C. Stamm, W. S. Lin, and K. J. R. Liu, "Forensics vs. Anti-Forensics: A Decision And Game Theoretic Framework", IEEE International Conference on Acoustic, Speech, and Signal Processing (ICASSP), Kyoto, Japan, March 2012, pp. 1749 - 1752.
  16. X. Chu, M. C. Stamm, W. S. Lin, and K. J. R. Liu, "Forensic Identification of Compressively Sensed Images", IEEE International Conference on Acoustic, Speech, and Signal Processing (ICASSP), Kyoto, Japan, March 2012, pp. 1837 - 1840.
  17. M. C. Stamm and K. J. R. Liu, "Anti-Forensics for Frame Deletion/Addition in MPEG Video", IEEE International Conference on Acoustic, Speech, and Signal Processing (ICASSP), Prague, Czech Republic, May 2011, pp. 1876 - 1879.
  18. M. C. Stamm and K. J. R. Liu, "Wavelet-Based Image Compression Anti-Forensics", IEEE International Conference on Image Processing (ICIP), Hong Kong, China, September 2010, pp. 1737 - 1740.
  19. M. C. Stamm, S. K. Tjoa, W. S. Lin, and K. J. R. Liu, "Undetectable Image Tampering Through JPEG Compression Anti-Forensics", IEEE Int. Conf. Image Processing (ICIP), Hong Kong, China, September 2010, pp. 2109 - 2112.
  20. M. C. Stamm, S. K. Tjoa, W. S. Lin, and K. J. R. Liu, "Anti-Forensics of JPEG Compression" , IEEE Int. Conf. Acoustic, Speech, and Signal Processing (ICASSP), Dallas, March 2010, pp. 1694 - 1697.
  21. M. C. Stamm and K. J. R. Liu, "Forensic Estimation and Reconstruction of a Contrast Enhancement Mapping" , IEEE Int. Conf. Acoustic, Speech, and Signal Processing (ICASSP), Dallas, March 2010, pp. 1698 - 1701.
  22. S. K. Tjoa, M. C. Stamm, W. S. Lin, and K. J. R. Liu, "Harmonic Variable-Size Dictionary Learning for Music Source Separation", IEEE Int. Conf. Acoustic, Speech, and Signal Processing (ICASSP), Dallas, March 2010, pp. 413 - 416.
  23. M. C. Stamm and K. J. R. Liu, "Forensic Detection of Image Tampering Using Intrinsic Statistical Fingerprints in Histograms", Proc. APSIPA Annual Summit and Conference, Sapporo, Japan, October 2009.
  24. M. C. Stamm and K. J. R. Liu, "Anti-Forensic Signal Processing", Proc. ARO Workshop on Digital Forensics, Arlington, VA, September 2009.
  25. M. Stamm and K. J. R. Liu, "Blind Forensics of Contrast Enhancement in Digital Images" , IEEE Int. Conf. Image Processing (ICIP), San Diego, USA, October 2008, pp. 3112 - 3115.