Abstract
Digital images can be easily tampered with image editing tools. The detection of tampering operations is of great importance. Passive digital image tampering detection aims at verifying the authenticity of digital images without any a prior knowledge on the original images. There are various methods proposed in this filed in recent years. In this paper, we present an overview of these methods in three levels, that is low level, middle level, and high level in semantic sense. The main ideas of the proposed approaches at each level are described in detail, and some comments are given.
Keywords
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References
Kundur, D., Hatzinakos, D.: Digital watermarking for telltale tamper proofing andauthentication. Proceedings of the IEEE 87(7), 1167–1180 (1999)
Rey, C., Dugelay, J.: A survey of watermarking algorithms for image authentication. EURASIP Journal on Applied Signal Processing 2002(6), 613–621 (2002)
Sencar, H.T., Memon, N.: Overview of state-of-the-art in digital image forensics, part of indian statistical institute platinum jubilee monograph series titled ’statistical science and interdisciplinary research (2008)
Chen, M., Fridrich, J., Goljan, M., Lukas, J.: Determining image origin and integrity using sensor noise. IEEE Transactions on Information Forensics and Security 3(1), 74–90 (2008)
Lin, Z., Wang, R., Tang, X., Shum, H.Y.: Detecting doctored images using camera response normality and consistency. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 1087–1092 (2005)
Farid, H.: Creating and detecting doctored and virtual images: Implications to the child pornography prevention act. Technical Report TR2004-518, Department of Computer Science, Dartmouth College (2004)
Li, Y., Sun, J., Tang, C., Shum, H.: Lazy snapping. In: International Conference on Computer Graphics and Interactive Techniques, pp. 303–308. ACM, New York (2004)
Ng, T.T., Chang, S.F., Lin, C.Y., Sun, Q.: Passive-blind image forensics. In: Multimedia Security Technologies for Digital Rights Management. Elsevier, Amsterdam (2006)
He, J., Lin, Z., Wang, L., Tang, X.: Detecting doctored JPEG images via DCT coefficient analysis. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3953, pp. 423–435. Springer, Heidelberg (2006)
Swaminathan, A., Wu, M., Liu, K.: Digital image forensics via intrinsic fingerprints. IEEE Trans. Info. Forensics and Security 3(1), 101–117 (2008)
Popescu, A., Farid, H.: Exposing digital forgeries in color filter array interpolated images. IEEE Transactions on Signal Processing 53(10), 3948–3959 (2005)
Popescu, A., Farid, H.: Exposing digital forgeries by detecting traces of resampling. IEEE Transactions on Signal Processing 53(2), 758–767 (2005)
Popescu, A., Farid, H.: Statistical tools for digital forensics. In: 6th International Workshop on Information Hiding, pp. 128–147. Springer, Heidelberg (2004)
Mahdian, B., Saic, S.: Blind authentication using periodic properties of interpolation. IEEE Transactions on Information Forensics and Security 3(3), 529–538 (2008)
Mahdian, B., Saic, S.: Detection and description of geometrically transformed digital images. In: Proc. SPIE, Media Forensics and Security, vol. 7254, pp. 72540J–72548J (2009)
Johnson, M., Farid, H.: Exposing digital forgeries through chromatic aberration. In: Proceedings of the 8th workshop on Multimedia and security, pp. 48–55. ACM, New York (2006)
Lukáš, J., Fridrich, J., Goljan, M.: Detecting digital image forgeries using sensor pattern noise. In: Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, vol. 6072, pp. 362–372 (2006)
Chen, M., Fridrich, J., Goljan, M., Lukas, J.: Determining image origin and integrity using sensor noise. IEEE Transactions on Information Forensics and Security 3(1), 74–90 (2008)
Swaminathan, A., Wu, M., Liu, K.: Non-intrusive component forensics of visual sensors using output images. IEEE Transactions on Information Forensics and Security 2(1), 91–106 (2007)
Swaminathan, A., Wu, M., Liu, K.: Component forensics of digital cameras: A non-intrusive approach. In: Annual Conference on Information Sciences and Systems, pp. 1194–1199 (2006)
Fu, D., Shi, Y., Su, W., et al.: A generalized Benford’s law for JPEG coefficients and its applications in image forensics. In: Proc. of SPIE Security, Steganography, and Watermarking of Multimedia Contents., vol. 6505, pp. 47–58 (2007)
Luo, W., Qu, Z., Huang, J., Qiu, G.: A novel method for detecting cropped and recompressed image block. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), vol. 2, pp. 217–220 (2007)
Ye, S., Sun, Q., Chang, E.: Detecting digital image forgeries by measuring inconsistencies of blocking artifact. In: IEEE International Conference on Multimedia and Expo, pp. 12–15 (2007)
Farid, H.: Exposing digital forgeries form jpeg ghosts. IEEE transactions on information forensics and security 4(1), 154–160 (2009)
Farid, H., Lyu, S.: Higher-order wavelet statistics and their application to digital forensics. In: IEEE Conference on Computer Vision and Pattern Recognition Workshop (2003)
Bayram, S., Avcıbaş, İ., Sankur, B., Memon, N.: Image manipulation detection. Journal of Electronic Imaging 15(4), 1–17 (2006)
Avcibas, I., Memon, N., Sankur, B.: Steganalysis using image quality metrics. IEEE transactions on Image Processing 12(2), 221–229 (2003)
Avcibas, I.: Image steganalysis with binary similarity measures. EURASIP Journal on Applied Signal Processing 2005(17), 2749–2757 (2005)
Lyu, S., Farid, H.: Steganalysis using higher-order image statistics. IEEE Transactions on Information Forensics and Security 1(1), 111–119 (2006)
Shi, Y.Q., Chen, C.-H., Xuan, G., Su, W.: Steganalysis versus splicing detection. In: Shi, Y.Q., Kim, H.-J., Katzenbeisser, S. (eds.) IWDW 2007. LNCS, vol. 5041, pp. 158–172. Springer, Heidelberg (2008)
Shi, Y., Chen, C., Chen, W.: A natural image model approach to splicing detection. In: Proceedings of the 9th workshop on Multimedia & security, pp. 51–62. ACM Press, New York (2007)
Farid, H.: Detecting digital forgeries using bispectral analysis. Technical report, MIT AI Memo AIM-1657, MIT (1999)
Ng, T.T., Chang, S.F., Sun, Q.: Blind detection of photomontage using higher order statistics. In: IEEE International Symposium on Circuits and Systems, vol. 5, pp. 688–691 (2004)
Ng, T.T., Chang, S.F.: A model for image splicing. In: IEEE International Conference on Image Processing, vol. 2, pp. 1169–1172 (2004)
Fridrich, J., Soukal, D., Lukas, J.: Detection of copy-move forgery in digital images. In: Digital Forensic Research Workshop (2003)
Popescu, A., Farid, H.: Exposing digital forgeries by detecting duplicated image regions. Technical report, Department of Computer Science, Dartmouth College
Bayram, S., Sencar, H.T., Memon, N.: An efficient and robust method for detecting copy-move forgery. In: IEEE International Conference on Acoustics, Speech, and Signal Processing. (2009)
Chen, W., Shi, Y., Su, W.: Image splicing detection using 2-d phase congruency and statistical moments of characteristic function. In: Security, Steganography and Watermarking of Multimedia Contents IX, Proceeding. of SPIE, San Jose, CA, USA (2007)
Hsiao, D., Pei, S.: Detecting digital tampering by blur estimation. In: International Workshop on Systematic Approaches to Digital Forensic Engineering, pp. 264–278 (2005)
Johnson, M., Farid, H.: Exposing digital forgeries by detecting inconsistencies in lighting. In: Proceedings of the workshop on Multimedia and security, pp. 1–10 (2005)
Johnson, M., Farid, H.: Exposing digital forgeries in complex lighting environments. IEEE Transactions on Information Forensics and Security 2(3), 450–461 (2007)
Johnson, M., Farid, H.: Exposing digital forgeries through specular highlights on the eye. In: International Workshop on Information Hiding (2007)
Gloe, T., Kirchner, M., Winkler, A., Böhme, R.: Can we trust digital image forensics? In: Proceedings of the 15th international conference on Multimedia, pp. 78–86. ACM, New York (2007)
Kirchner, M., Bohme, R.: Tamper hiding: Defeating image forensics. In: Furon, T., Cayre, F., Doërr, G., Bas, P. (eds.) IH 2007. LNCS, vol. 4567, pp. 326–341. Springer, Heidelberg (2008)
Ng, T., Chang, S., Sun, Q.: A data set of authentic and spliced image blocks. Technical report, DVMM, Columbia University (2004), http://www.ee.columbia.edu/ln/dvmm/downloads/AuthSplicedDataSet/photographers.htm
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Wang, W., Dong, J., Tan, T. (2009). A Survey of Passive Image Tampering Detection. In: Ho, A.T.S., Shi, Y.Q., Kim, H.J., Barni, M. (eds) Digital Watermarking. IWDW 2009. Lecture Notes in Computer Science, vol 5703. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03688-0_27
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DOI: https://doi.org/10.1007/978-3-642-03688-0_27
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