Abstract
In this paper, a simple yet effective anti-forensic scheme capable of misleading double JPEG compression detection techniques is proposed. Based on image resizing with bilinear interpolation, the proposed operation aims at destroying JPEG grid structure while preserving reasonably good image quality. Given a doubly compressed image, our attack modifies the image by JPEG decompressing, shrinking and zooming the image with bilinear interpolation before JPEG compression with the same quality factor as used in the given image. The efficacy of the proposed scheme has been evaluated on two prominent double JPEG detection techniques and the outcome reveals that the proposed scheme is mostly effective, especially in the cases that the first quality factor is lower than the second quality factor.
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References
Stamm, M.C., Tjoa, S.K., Lin, W.S., Liu, K.J.R.: Anti-Forensics of JPEG Compression. In: IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), pp. 1694–1697. IEEE Press, New York (2010)
Stamm, M.C., Tjoa, S.K., Lin, W.S., Liu, K.J.R.: Undetectable Image Tampering Through JPEG Compression. In: IEEE International Conference on Image Processing (ICIP), pp. 2109–2112. IEEE Press, New York (2010)
Stamm, M.C., Liu, K.J.R.: Anti-Forensics of Digital Image Compression. IEEE Transactions on Information Forensics and Security 6, 1050–1065 (2011)
Popescu, A.C.: Statistical Tools for Digital Image Forensics. PhD Thesis, Darmouth College, Hanover, NH, USA (advised by H. Farid) (December 2004)
Huang, F., Huang, J., Shi, Y.Q.: Detecting Double JPEG Compression with the Same Quantization Matrix. IEEE Transactions on Information Forensics and Security 5, 848–856 (2010)
Chen, C., Shi, Y.Q., Su, W.: A Machine Learning Based Scheme for Double JPEG Compression Detection. In: International Conference on Pattern Recognition (ICPR), pp. 1–4. IEEE Press, New York (2008)
Bin, L., Shi, Y.Q., Huang, J.: Detecting Doubly Compressed JPEG Images by Using Mode Based First Digit Features. In: IEEE Workshop on Multimedia Signal Processing (MMSP), pp. 730–733. IEEE Press, New York (2008)
Schaefer, G., Stich, M.: UCID: an Uncompressed Color Image Database. In: Proc. SPIE, Storage and Retrieval Methods and Applications for Multimedia, San Jose, USA, pp. 472–480 (2004)
Chang, C.C., Lin, C.J.:LIBSVM : a library for support vector machines. ACM Transactions on Intelligent Systems and Technology (2011), Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm
Fridrich, J., Goljan, M., Hogea, D.: Steganalysis of JPEG Images: Breaking the F5 Algorithm. In: Petitcolas, F.A.P. (ed.) IH 2002. LNCS, vol. 2578, pp. 310–323. Springer, Heidelberg (2003)
Fridrich, J.: Feature-Based Steganalysis for JPEG Images and Its Implications for Future Design of Steganographic Schemes. In: Fridrich, J. (ed.) IH 2004. LNCS, vol. 3200, pp. 67–81. Springer, Heidelberg (2004)
Sutthiwan, P., Shi, Y.Q., Dong, J., Tan, T., Ng, T.T.: New Developments in Color Image Tampering Detection. In: IEEE International Symposium on Circuits and Systems, pp. 3064–3067. IEEE Press, New York (2010)
Sutthiwan, P., Shi, Y.Q., Su, W., Ng, T.T.: Rake Transform and Edge Statistics for Image Forgery Detection. In: Workshop on Content Protection and Forensics, IEEE International Conference on Multimedia and Expo., pp. 1463–1468. IEEE Press, New York (2010)
Sutthiwan, P., Shi, Y.Q., Zhao, H., Ng, T.-T., Su, W.: Markovian Rake Transform for Digital Image Tampering Detection. In: Shi, Y.Q., Emmanuel, S., Kankanhalli, M.S., Chang, S.-F., Radhakrishnan, R., Ma, F., Zhao, L. (eds.) Transactions on DHMS VI. LNCS, vol. 6730, pp. 1–17. Springer, Heidelberg (2011)
Columbia DVMM Research Lab: Columbia Image Splicing Detection Evaluation Dataset (2004), http://www.ee.columbia.edu/ln/dvmm/downloads/AuthSpliced-DataSet/AuthSplicedDataSet.htm
CASIA Tampered Image Detection Evaluation Database (2010), http://forensics.idealtest.org
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Sutthiwan, P., Shi, Y.Q. (2012). Anti-Forensics of Double JPEG Compression Detection. In: Shi, Y.Q., Kim, HJ., Perez-Gonzalez, F. (eds) Digital Forensics and Watermarking. IWDW 2011. Lecture Notes in Computer Science, vol 7128. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32205-1_33
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DOI: https://doi.org/10.1007/978-3-642-32205-1_33
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