Abstract
Identifying the originating device for a given media, i.e. the type, brand, model and other characteristics of the device, is currently one of the important fields of digital forensics. This paper proposes a forensic technique based on the Benford’s law to identify the printer’s brand and model from the printed-and-scanned images at which the first digit probability distribution of multi-size block DCT coefficients are extracted that constitutes a feature vector as the input to support vector machine (SVM) classifier. The proposed technique is different from the traditional use of noise feature patterns appeared in the literature. It uses as few as nine numbers of forensic features representing each printer by leveraging properties of the Benford’s law for printer identification. Experiments conducted over electrophotographic (EP) printers and deskjet printers achieve an average of 96.0% classification rate of identification for five distinct printer brands and an average of 94.0% classification rate for six diverse printer models out of those five brands.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Khanna, N., Mikkilineni, A.K., Chiu, G.T., Allebach, J.P., Delp, E.J.: Survey of scanner and printer forensics at purdue university. In: Srihari, S.N., Franke, K. (eds.) IWCF 2008. LNCS, vol. 5158, pp. 22–34. Springer, Heidelberg (2008)
Zhao, X., Ho, A.T.S., Shi, Y.Q.: Image forensics using generalized benfords law for accurate detection of unknown jpeg compression in watermarked images. In: 16th International Conference on Digital Signal Processing (DSP), Greece (July 2009)
Chiang, P.-J., Khanna, N., Mikkilineni, A., Segovia, M., Suh, S., Allebach, J., Chiu, G., Delp, E.: Printer and scanner forensics. IEEE Signal Processing Magazine 26, 72–83 (2009)
Mikkilineni, A.K., Arslan, O., Chiang, P.-J., Kumontoy, R.M., Allebach, J.P., Chiu, G.T.-C., Delp, E.J.: Printer forensics using svm techniques. In: Proceedings of the IS&T’s NIP21: International Conference on Digital Printing Technologies, Baltimore, MD, vol. 21, pp. 223–226 (October 2005)
Mikkilineni, A.K., Chiang, P.-J., Ali, G.N., Chiu, G.T.-C., Allebach, J.P., Delp, E.J.: Printer identification based on graylevel co-occurrence features for security and forensic applications. In: Security, Steganography, and Watermarking of Multimedia Contents, pp. 430–440 (2005)
Nitin, K., Mikkilineni, A.K., Chiang, P.-J., Ortiz, M.V., Shah, V., Suh, S., Chiu, G.T.-C., Allebach, J.P., Delp, E.J.: Printer and sensor forensics. In: IEEE Workshop on Signal Processing Applications for Public Security and Forensics, Washington, D.C, USA, April 11-13 (2007)
Bulan, O., Mao, J., Sharma, G.: Geometric distortion signatures for printer identification. In: Proc. IEEE Intl. Conf. Acoustics Speech and Sig. Proc., Taipei, Taiwan, pp. 1401–1404 (2009)
Lukas, J., Fridrich, J., Goljan, M.: Digital camera identification from sensor pattern noise. IEEE Transactions on Information Forensics and Security 1, 205–214 (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, 74–90 (2008)
Filler, T., Fridrich, J., Goljan, M.: Using sensor pattern noise for camera model identification. In: 15th IEEE International Conference on Image Processing, ICIP 2008, pp. 1296–1299 (12-15, 2008)
Perez-Gonzalez, F., Heileman, G., Abdallah, C.: Benford’s law in image processing. In: Proc. IEEE International Conference on Image Processing, vol. 1, pp. 405–408 (2007)
Fu, D., Shi, Y.Q., Su, W.: A generalized Benford’s law for JPEG coefficients and its applications in image forensics. In: Proceedings of SPIE, vol. 6505, p. 65051L (2007)
Floyd, R., Steinberg, L.: An adaptive algorithm for spatial greyscale. Proceedings of the. Society for Information Display 17(2), 75–77 (1976)
Ulichney, R.: Digital Halftoning. MIT Press, Cambridge (1987)
Li, B., Shi, Y.Q., Huang, J.: Detecting double compressed jpeg image by using mode based first digit features. In: IEEE International Workshop on Multimedia Signal Processing (MMSP 2008), Queensland, Australia, pp. 730–735 (October 2008)
Chen, P.-H., Lin, C.-J.: LIBSVM: a library for support vector machines (2001) Software available at, http://www.csie.ntu.edu.tw/~cjlin/libsvm
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Jiang, W., Ho, A.T.S., Treharne, H., Shi, Y.Q. (2010). A Novel Multi-size Block Benford’s Law Scheme for Printer Identification. In: Qiu, G., Lam, K.M., Kiya, H., Xue, XY., Kuo, CC.J., Lew, M.S. (eds) Advances in Multimedia Information Processing - PCM 2010. PCM 2010. Lecture Notes in Computer Science, vol 6297. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15702-8_59
Download citation
DOI: https://doi.org/10.1007/978-3-642-15702-8_59
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15701-1
Online ISBN: 978-3-642-15702-8
eBook Packages: Computer ScienceComputer Science (R0)