Journal of Systems Science and Complexity

, Volume 28, Issue 5, pp 1164–1176 | Cite as

The detecting system of image forgeries with noise features and EXIF information

  • Xiaoting Sun
  • Yezhou Li
  • Shaozhang Niu
  • Yanli Huang
Article

Abstract

Recently, the digital image blind forensics technology has received an increasing attention in academic community. This paper aims at developing a new identification approach based on the statistical noise and exchangeable image file format (EXIF) information of image for images authentication. In particular, the authors can identify whether the current image has been modified or not by utilizing the relevance between noise and EXIF parameters and comparing the real values with the estimated values of the EXIF parameters. Experimental results validate the proposed method. That is, the detecting system can identify the doctored image effectively.

Keywords

Blind forensics doctored image EXIF parameters noise features 

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References

  1. [1]
    Hussain M, Muhammad G, Saleh S Q, et al., Copy-move image forgery detection using multiresolution weber descriptors, The 8th International Conference on Singnal Image Technology and Internet Based Systems, 2012, 395–401.Google Scholar
  2. [2]
    Bora R M and Shahane N M, Image forgery detection through motion blur estimates, IEEE International Conference on Computational Intelligence and Computing Research, 2012, 1–4.Google Scholar
  3. [3]
    Li Y Z, Wu X M, Niu S Z, et al., Detecting forgeries of Chinese character based on camera calibration, The Journal of Beijing Universities of Posts and Telecommunications, 2012, 35(6): 16–19.CrossRefGoogle Scholar
  4. [4]
    Johnson M K and Farid H, Exposing digital forgeries in complex lighting environments, IEEE Transactions on Information Forensics and Security, 2007, 2: 450–461.CrossRefGoogle Scholar
  5. [5]
    Popescu A C and Farid H, Exposing digital forgeries by detecting traces of re-sampling, IEEE Trans. Signal Processing, 2005, 53(2): 758–767.MathSciNetCrossRefGoogle Scholar
  6. [6]
    Popescu A C and Farid H, Exposing digital forgeries in color filter array interpolated images, IEEE Transactions on Signal Processing, 2005, 53(10): 3948–3959.MathSciNetCrossRefGoogle Scholar
  7. [7]
    Valenzise G, Tagliasacchi M, and Tubaro S, Revealing the traces of JPEG compression antiforensics, IEEE Trans. Information Forensics and Security, 2013, 8(2): 335–349.CrossRefGoogle Scholar
  8. [8]
    Huang F, Huang J, and Yun Q, Detecting double JPEG compression with the same quantization matri, IEEE Trans. Information Forensics and Security, 2010, 5(4): 848–856.CrossRefGoogle Scholar
  9. [9]
    Johnson M K and Farid H, Detecting photographic composites of people, Digital Watermarking, Lecture Notes in Computer Science, 2008, 5041: 19–33.CrossRefGoogle Scholar
  10. [10]
    Kee E, O’Brien J, and Farid H, Exposing photo manipulation with inconsistent shadows, ACM Transaction on Graphics, 2013, 32(4): 1–11.CrossRefGoogle Scholar
  11. [11]
    Zhao J and Kang W, Detection algorithm of image forgery based on principal components analysis of projection data, Computer Engineering, 2012, 38(10): 203–205.MathSciNetGoogle Scholar
  12. [12]
    Kee E, Johnson M K, and Farid H, Digital image authentication from jpeg headers, IEEE Trans. Inf. Forensics Security, 2011, 6(3): 1066–1075.CrossRefGoogle Scholar
  13. [13]
    Fan J Y, Cao H, and Sattar F, Modeling the EXIF-image correlation for image manipulation detection, IEEE Press, 2011, 1945–1948.Google Scholar
  14. [14]
    Lü J H, Chen G R, and Zhang S C, A unified chaotic system and its research, Journal of the Graduate School of the Chinese Academy of Science, 2003, 20(1): 123–129.Google Scholar
  15. [15]
    Lü J H, Mathematical models and synchronization criterions of complex dynamical networks, Journal of Systems Engineering — Theory and Practice, 2004, 24(4): 17–22.Google Scholar
  16. [16]
    Wang P, Li D M, Wu X Q, and Lv J H, Estimating the ultimate bound for the generalized quadratic autonomous chaotic systems, Proceedings of the 29th Chinese Control Conference, 2010, 791–795.Google Scholar
  17. [17]
    Holst G C and Lomheim T S, CMOS/CCD Sensors and Camera Systems, Society of Photo Optical, 2007.Google Scholar

Copyright information

© Institute of Systems Science, Academy of Mathematics and Systems Science, CAS and Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Xiaoting Sun
    • 1
  • Yezhou Li
    • 1
  • Shaozhang Niu
    • 2
  • Yanli Huang
    • 2
  1. 1.School of ScienceBeijing University of Posts and TelecommunicationsBeijingChina
  2. 2.Beijing Key Lab of Intelligent Telecommunication Software and MultimediaBeijing University of Posts and TelecommunicationsBeijingChina

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