Abstract
At recently, the most of the digital images are stored and transferred in their compressed format using discrete cosine transform (DCT)-based compression technique. DCT is one of the most important data compression technique due to the efforts from Joint Photographic Experts Group(JPEG). Blind steganalysis means how to detect the presence of the messages that are hidden using different types of steganography algorithms and has the ability to detect new unknown steganography algorithms. This paper presents blind steganalysis technique that can reliably detect the existence of messages hidden in JPEG files. In order to save the computation and memory cost, it is desirable to have image processing operations implemented directly in the DCT domain. The proposed method is based on extracting features directly from DCT domain through the analysis of differences between DCT coefficients before and after cropping. The extracted features are prepared as input to Support Vector Machine (SVM) to classify the image as stego (image that contain secret message) or clean (image that does not contain secret message). The experiments performed show that the proposed method yields better classification accuracy compared with other related works.
Similar content being viewed by others
References
Bhme R, Westfeld A (2004) Breaking cauchy model-based jpeg steganography with first order statistics. Proceedings of 9th Eur. Symp. Research computer security (ESORICS). Sophia Antipolis, France 3193:125–140. doi:10.1007/978-3-540-30108-0_8
Cai K, Li X, Zeng T, Yang B, Lu X (2010) Reliable histogram features for detecting LSB matching. Image processing (ICIP), 2010 17th IEEE international conference on, pp 1761–1764. doi:10.1109/ICIP.2010.5651567
Chang C-C, Lin C-J (2001) LIBSVM a library for support vector machines http://www.csie.ntu.edu.tw/~cjlin/libsvm. Accessed 1 Oct 2013
Chen GM, Chen Q, Zhang D, Zhou DN (2014) Steganalysis based on distribution characters of stego-images in reduced dimension space. Multimedia Tools and Applications 71:497–515
Chutani S, Goyal H (2012) Lsb embedding in spatial domain - a review of improved techniques. International Journal of Computers & Technology 3:153–157
European southern observatory (ESO) photo gallery. http://www.eso.org/public/images/. Accessed 1 Oct 2015
Fridrich J (2005) Feature-based steganalysis for jpeg images and its implications for future design of steganographic schemes. Information Hiding, Springer 3200:67–81. doi:10.1007/978-3-540-30114-1_6
Fridrich J, Goljan M, Du R (2001) Detecting LSB steganography in color, and gray-scale images. MultiMedia, IEEE 8:22–28. doi:10.1109/93.959097
Fridrich J, Goljan M, Hogea D (2002) Steganalysis of jpeg images: breaking the f5 algorithm. Proceedings of 5th Int. Workshop Information Hiding 2578:310–323. doi:10.1007/3-540-36415-3_20
Fridrich J, Goljan M, Hogea D, Soukal D (2003) Quantitative steganalysis of digital images: estimating the secret message length. Multimedia Systems, Springer 9:288–302. doi:10.1007/s00530-003-0100-9
Fridrich J, Goljan M, Soukal D (2005) Perturbed quantization steganography. Multimedia Systems, Springer 11:98–107. doi:10.1007/s00530-005-0194-3
Fridrich J, Pevn T, Kodovsk J (2007) Statistically undetectable jpeg steganography: dead ends, challenges, and opportunities. Proceedings of 9th ACM Multimedia & Security Workshop, pp 3–14
Hamid N, Yahya A, Ahmad B, Al-qershi O (2012) Image steganography techniques: an overview. International Journal of Computer Science and Security (IJCSS) 6:168–187
Hetzl S, Mutzel P (2005) A graph-theoretic approach to steganography. Communications and Multimedia Security, Springer 3677:119–128. doi:10.1007/11552055_12
Hsu C, Chang C, Lin C (2003) A practical guide to support vector classification http://www.csie.ntu.edu.tw/~cjlin/papers/guide/guide.pdf. Accessed 1 Oct 2013
Huang Q, Ouyang W (2010) Protect fragile regions in steganography LSB embedding. In 3rd international symposium on knowledge acquisition and modeling, pp 175–178
Jiang J, Feng G (2002) The spatial relationship of dct coefficients between a block and its sub-blocks. Signal Processing, IEEE Transactions on 50:1160–1169. doi:10.1109/78.995072
Johnson NF, Katzenbeisser SC (2000) A survey of steganographic techniques. Information Hiding Techniques for Steganography and Digital Watermarking, pp:43–78
A. Latham, Jphide& seek. http://linux01.gwdg.de/~alatham/stego.html
Lerch-Hostalot D, Megas D (2013) LSB matching steganalysis based on patterns of pixel differences and random embedding. Computers & Security 32:192–206. doi:10.1016/j.cose.2012.11.005
Li B, Shi Y, Huang JW (2009) Steganalysis of YASS. IEEE Transactions on Information Forensics and Security 4:369–382. doi:10.1109/TIFS.2009.2025841
Li B, He J, Huang J, Shi YQ (2011) A survey on image steganography and steganalysis. Information Hiding and Multimedia Signal Processing 2:142–172
Liu Q, Sung A, Qiao M, Chen Z, Ribeiro B (2010) An improved approach to steganalysis of JPEG images. Inf Sci 180:1643–1655
Luo W, Huang F, Huang J (2011) A more secure steganography based on adaptive pixelvalue differencing scheme. Multimedia Tools and Applications 52:407–430
Meghanathan N, Nayak L (2010) Steganalysis algorithms for detecting the hidden information in image, audio and video cover media. International Journal of Network Security & Its Application 2:43–55
Mielikainen J (2006) LSB matching revisited. IEEE Signal Process Lett 13:285–287
National resource conservation system (NRCS) photo gallery. http://photogallery.nrcs.usda.gov. Accessed 1 Oct 2015
Pevn T, Fridrich J (2005) Towards multi-class blind steganalyzer for jpeg images. Digital Watermarking, Springer 3710:39–53. doi:10.1007/11551492_4
Sharma M, Bera S (2012) A review on blind still image steganalysis techniques using features extraction and pattern classification method. International Journal of Computer Science, Engineering and Information Technology 2:117–135. doi:10.5121/ijcseit.2012.2308
Sharp T (2001) An implementation of key based digital signal steganography. Proceedings Information Hiding Workshop, Springer LNCS 2137:13–26. doi:10.1007/3-540-45496-9_2
Wang K, Lu ZM, Hu YJ (2013) A high capacity lossless at hiding scheme for jpeg images. J Syst Softw 86:1965–1975
Wang R, Xu M, Ping X, Zhang T (2015) Steganalysis of jpeg images by block texture based segmentation. Multimedia Tools and Applications 74:5725–5746
Westfeld A (2001) F5-a steganographic algorithm (high capacity despite bet-tersteganalysis). Information Hiding, Springer 2137:289–302. doi:10.1007/3-540-45496-9_21
Xi L, Ping X, Zhang T (2010) Improved LSB matching steganography resisting histogram attacks. IEEE, pp 203–206
Zeng XT, Ping LD, Pan XZ (2010) A lossless robust data hiding scheme. Pattern Recogn 43:1656–1667
Zhang J, Hu Y, Yuan Z (2009) Detection of LSB matching steganography using the envelope of histogram. Journal of Computers 4:646–653. doi:10.4304/jcp.4.7.646-653
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Rabee, A.M., Mohamed, M.H. & Mahdy, Y.B. Blind JPEG steganalysis based on DCT coefficients differences. Multimed Tools Appl 77, 7763–7777 (2018). https://doi.org/10.1007/s11042-017-4676-z
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-017-4676-z