Most improved steganographies based on intelligent optimization cannot realize high-dimensional features optimization simultaneously. To solve the problem, this paper proposes an improved LSB±k steganography (denoted SFLA-LSB±k) based on SFLA to achieve an optimal decision surface. Different from the other improved steganographies that attempt to keep image features unchanged after data embedding as much as possible, the proposed method tries to randomly change feature directions of stego-image in the embedding process optimized by SFLA. Thus, it is difficult to find a decision surface to distinguish cover images from stego-images. Simulation indicates that, with the same embedding capacity, SFLA-LSB±k demonstrates better performance in resisting steganalysis than the traditional LSB±k and the improved LSB±k optimized by PSO. Especially, the AUC value is reduced to 0.5637 when k=1 against steganalysis with 78-dimension features.
OUYANG Chun-juan, LIU Chang-xin, LIU Huan
. Improved LSB±k Steganography Based on Decision Surface Optimized by SFLA[J]. Journal of Applied Sciences, 2015
, 33(6)
: 663
-670
.
DOI: 10.3969/j.issn.0255-8297.2015.06.010
[1] 王朔中,张新鹏,张卫明.以数字图像为载体的隐写分析研究进展[J].计算机学报, 2009, 32(7):1247-1263. Wang S Z, Zhang X P, Zhang W M. Recent advances in image-based steganalysis research[J]. Chinese Journal of Computers, 2009, 32(7):1247-1263. (in Chinese)
[2] Filler T, Judas J, Fridrich J. Minimizing additive distortion in steganography using syndrome-trellis codes[J]. IEEE Transactions on Information Forensics and Security, 2011, 6(3):920-935.
[3] Fridrich J, Kodivsky J, Holub V. Rich models for steganalysis of digital images[J]. IEEE Transactions on Information and Security, 2012, 7(3):868-882.
[4] Sharp T. An implementation of key-based digital signal steganography[C]//the 4th International Workshop on Information Hiding. Pittsburgh, 2001, 2137:13-26.
[5] Li X X, Wang J J. A steganographic method based upon JPEG and particle swarm optimization algorithm[J]. Information Sciences, 2007, 177(15):3099-3109.
[6] Liu G J, Zhang Z. Improved LSB-matching steganography for preserving second-order statistics[J]. Journal of Multimedia, 2010, 5(5):458-463.
[7] Guo Y Q, Kong X W, You X G. Secure steganography based on binary particle swarm optimization[J]. Journal of Electronics, 2009, 26(2):285-288.
[8] 于丽芳,赵耀,倪蓉蓉.基于粒子群算法和改进PM1的JPEG图像中的安全密写方法[J].南京邮电大学学报:自然科学版, 2009, 29(3):49-53. Yu L F, Zhao Y, Ni R R. Secure steganography in JPEG images based on PSO and improved PM1[J]. Journal of Nanjing University of Posts and Telecommunications:Natural Science, 2009, 29(3):49-53. (in Chinese)
[9] Ghasemi E, Shanbehzadeh J, Jamshid F. High capacity image steganography based on genetic algorithm and wavelet transform[J]. Intelligent Control and Innovative Computing, 2012, 110:395-404.
[10] Eusuff M M, Lansey K E. Optimization of water distribution network design using the shuffled frog leaping algorithm[J]. Journal of Water Sources Planning and Management, 2003, 129(3):210-225.
[11] United States Department of Agriculture. Natural resources conservation service photo gallery, http://photogallery.nrcs.usda.gov, 2002.
[12] Ker A D. Steganalysis of LSB matching in grayscale images[J]. IEEE Signal Processing Letters, 2005, 12(6):441-444.
[13] Xuan G R, Shi Y Q. Steganalysis based on multiple features formed by statistical moments of wavelet characteristic functions[J]. Comuter Science, 2005, 3727:262-265.
[14] Penvy T, Bas P, Fridrich J. Steganalysis by subtractive pixel adjacency matrix[J]. IEEE Transactions on Information Forensics and Security, 2010, 5(2):215-224.
