Adaptive batch steganography considering image embedding capacity

Optical Engineering

Volumn 48, Issue 8, 2009, Pages

  Sajedi, Hedieh ^a   Jamzad, Mansour ^a  

^a SHARIF UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

batch steganography; embedding capacity; ensemble methods; multiple cove images; steganalysis; support vector machine

Indexed keywords

BATCH STEGANOGRAPHY; EMBEDDING CAPACITY; ENSEMBLE METHODS; MULTIPLE COVE IMAGES; STEGANALYSIS; SUPPORT VECTOR;

CONTENT BASED RETRIEVAL;

STEGANOGRAPHY;

EID: 80055086123     PISSN: 00913286     EISSN: 15602303     Source Type: Journal    
DOI: 10.1117/1.3204231     Document Type: Article

References (32)

1. A., Westfeld, " F5-a steganographic algorithm: high capacity despite better steganalysis, " in, Proc. of 4th Int. Workshop on Information Hiding, Vol. 2137, pp. 289-302, Springer, Berlin/Heidelberg (Apr. 2001). (Pubitemid 33367674)
2. P., Sallee, " Model-based steganography, " in, Proc. of Int. Workshop on Digital Watermarking, Seoul, Vol. 2939, pp. 154-167, Springer, Berlin/Heidelberg (Oct. 2003). (Pubitemid 38334550)
3. J., Fridrich, M., Goljan, and D., Soukal, " Perturbed quantization steganography with wet paper codes, " in, Proc. ACM, Multimedia Workshop, Germany, pp. 4-15, ACM, New York (2004). (Pubitemid 40338445)
4. K., Solanki, A., Sarkar, and B. S., Manjunath, " YASS: yet another steganographic scheme that resists blind steganalysis, " in, Proc. of 9th Int. Workshop on Information Hiding, Saint Malo, Brittany, France, Vol. 4567/2008, pp. 16-31, Springer, Berlin/Heidelberg (Jun. 2007).
5. H., Sajedi and M., Jamzad, " Adaptive steganography method based on contourlet transform, " in, Proc. of 9th Int. Conf. Signal Processing, pp. 745-748, IEEE, Beijing (2008).
6. R., Chandramouli and N. D., Memon, " Steganography capacity: a steganalysis perspective, ", Proc. SPIE, 5020, 173-177 (2003). spi PSISDG 0277-786X 10.1117/12.479732
7. J., Fridrich, T., Pevny, and J., Kodovsky, " Statistically undetectable JPEG steganography: dead ends, challenges, and opportunities, " in, Proc. of 10th ACM Workshop on Multimedia and Security (MM&Sec'08), Dallas, pp. 3-14, ACM, New York (Sept. 2007). (Pubitemid 351203799)
8. C., Cachin, " An information-theoretic model for steganography, " in, Proc. of 2nd Int. Workshop on Information Hiding, Prtland, OR, Vol. 1525/1998, pp. 306-318, Springer, Berlin/Heidelberg (Apr. 1998).
9. P., Moulin and M. K., Mihcak, " A framework for evaluating the data hiding capacity of image sources, ", IEEE Trans. Image Process., 11, 1029-1042 (2002). iei IIPRE4 1057-7149 10.1109/TIP.2002.802512 (Pubitemid 35250386)
10. A. D., Ker, " Batch Steganography and pooled steganalysis, " in, Proc. of 8th Information Hiding Workshop, IH 2006, Alexandria, VA, pp. 265-281, Springer, Berlin/Heidelberg (Jul. 2006).
11. A. D., Ker, " Perturbation hiding and the batch steganography problem, " in, Proc. of 10th Information Hiding Workshop, IH 2008, Santa Barbara, CA, pp. 45-59, Springer, Berlin/Heidelberg (May, 2008).
12. Y., Dong and K., Han, " Boosting SVM classifiers by ensemble, " in, Proc. of 14th Int. Conf. ACM on World Wide Web, pp. 1072-1073, ACM, New York (2005).
13. A. D., Ker, " A capacity result for batch steganography, ", IEEE Signal Process. Lett., 14 (8), 525-528 (2007). isp ISPLEM 1070-9908 10.1109/LSP.2006.891319 (Pubitemid 47250022)
14. A., Martin, G., Sapiro, and G., Seroussi, " Is image steganography natural? " Tech. Report, Information Theory Research Group, HP Laboratories Palo Alto (2004).
15. T., Qing and W., Jue, " A new fuzzy support vector machine based on the weighted margin, ", Neural Process. Lett., 20 (3), 139-150 (2004). 10.1007/s11063-004-1640-5
16. L., Zhang, F., Lin, and B., Zhang, " Support vector machine learning for image retrieval, " in, Proc. IEEE Int. Conf. on Image Processing, pp. 721-724, IEEE, Piscataway, NJ (2001). (Pubitemid 33057807)
17. C. J. C., Burges, " A tutorial on support vector machines for pattern recognition, ", Data Min. Knowl. Discov., 2, 121-167 (1998). awj DMKDFD 1384-5810 10.1023/A:1009715923555 (Pubitemid 128126769)
18. D., Meyer, F., Leisch, and K., Hornik, " The support vector machine under test, ", Neurocomputing, 55, 169-186 (2003). 9g3 NRCGEO 0925-2312 10.1016/S0925-2312(03)00431-4 (Pubitemid 37336675)
19. M., Kharrazi, T. H., Sencar, and N., Memon, " Benchmarking steganographic and steganalysis techniques, " in, Security, Steganography, and Watermarking of Multimedia Contents VII, Proc. SPIE, 5681, 252-263 (2005). spi PSISDG 0277-786X 10.1117/12.587375 (Pubitemid 40952986)
20. I., Avcibas, M., Kharrazi, N., Memon, and B., Sankur, " Image steganalysis with binary similarity measures, ", EURASIP J. Appl. Signal Process. 2005, 2749-2757 (2005). cws ZZZZZZ 1110-8657 10.1155/ASP.2005.2749 (Pubitemid 44178258)
21. S., Lyu and H., Farid, " Detecting hidden messages using higher-order statistics and support vector machines, " in, Proc. of 5th Int. Workshop on Information Hiding, The Netherlands, pp. 340-354, Springer-Verlag (Oct. 2002).
22. S., Lyu and H., Farid, " Steganalysis using color wavelet statistics and one-class support vector machines, " in, Security Steganography, and Watermarking of Multimedia Contents VI, Proc. SPIE, 5306, 35-45 (2004). spi PSISDG 0277-786X 10.1117/12.526012
23. J., Fridrich, " Feature-based steganalysis for jpeg images and its implications for future design of steganographic schemes, in, ", Proc. of 6th Int. Workshop on Information Hiding, Toronto, Ontario, Canada, pp. 67-81, Springer, Berlin/Heidelberg (May, 2004). (Pubitemid 39745168)
24. T. G., Dietterich, " Ensemble methods in machine learning, " in, Multiple Classifier Systems, Lect. Notes Comput. Sci., 1857, 1-15, (2001). 9fi LNCSD9 0302-9743 10.1007/3-540-45014-9-1
25. Y., Freund and R., Schapire, " A short introduction to boosting, ", J. Jpn. Soc. Artif. Intell., 14 (5), 771-780 (1999).
26. A. D., Ker, T., Penvy, J., Kodovsky, and J., Fridrich, " The square root law of steganographic capacity, " in, Proc. of International Multimedia Conf. 10th ACM Workshop on Multimedia and Security, Oxford, UK, pp. 107-116, ACM, New York (2008).
27. T., Pevny and J., Fridrich, " Merging Markov and DCT features for multi-class JPEG steganalysis, " in, Security, Forensics, Steganography, and Watermarking of Multimedia Contents X, Proc. SPIE, 6819, 681901 (2008). spi PSISDG 0277-786X 10.1117/12.793470
28. C., Chen, Y. Q., Shi, W., Chen, and G., Xuan, " Statistical moments based universal steganalysis using JPEG-2D array and 2-D characteristic function, " in, Proc. of ICIP, Atlanta, IEEE, pp. 105-108 (2006).
29. G., Xuan, Y. Q., Shi, J., Gao, D., Zou, C., Yang, C., Yang, Z., Zhang, P., Chai, C., Chen, and W., Chen, " Steganalysis based on multiple features formed by statistical moments of wavelet characteristic functions, " in, Proc. of 7th Int. Workshop on Information Hiding, Barcelona, Spain, Vol. 3727/2005, pp. 262-277, Springer-Verlag GmbH (Jun. 2005).
30. H., Sajedi and M., Jamzad, " A steganalysis method based on contourlet transform coefficients, " in, Proc. of 4th Int. Conf. on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), Harbin, China, pp. 245-248, IEEE Computer Society, Washington, DC (2008).
31. Washington University Image Database, 〈 http://www.cs.washington. edu/research/imagedatabase 〉.
32. M., Jamzad and F., Yaghmaee, " Achieving higher stability in watermarking according to image complexity, ", Scientia Iranica J., 13 (4), 404-412 (2006). (Pubitemid 46321900)