基于图像分类的鲁棒无载体信息隐藏

doi:10.3969/j.issn.0255-8297.2021.06.002

Abstract

Abstract: Aiming at the problem that traditional information hiding is difficult to resist the detection of steganalysis algorithms, this paper proposes a coverless data hiding method based on image classification and scale-invariant feature transform (SIFT) extraction. Firstly, an original image database is classified by using Faster R-CNN to generate different kinds of sub-image databases. Secondly, a robust hashing scheme is designed by using the direction information of SIFT feature points of the image, with which the image hash value of each sub-image database is calculated, and all images in each sub-image databases are mapped to corresponding binary hash values. Finally, secret information is divided into several segments, and by comparing the secret information segments with the binary hash values of all the images, the images corresponding to the secret information segments are retrieved from the sub-image database. These images are transmitted to the receiver as the carrier containing the secret to complete the information hiding process. The receiver receives all the stego-images, and extracts the secret information according to the agreed hashing scheme. Experimental results and analysis show that the proposed method is robust to JPEG compression, Gaussian noise, salt and pepper noise, image scaling and other attacks, and the performance of hiding capacity is also improved.

Key words: coverless information hiding, image classification, image hashing, robustness, hiding capacity

CLC Number:

TP309

DONG Tenglin, LI Xinran, YAO Heng, QIN Chuan. Robust Coverless Information Hiding Based on Image Classification[J]. Journal of Applied Sciences, 2021, 39(6): 893-905.

References

[1] 沈昌祥, 张焕国, 冯登国. 信息安全综述[J]. 中国科学, 2007, 37(2):129-150. Shen C X, Zhang H G, Feng D G. A survey of information security[J]. Science China, 2007, 37(2):129-150. (in Chinese)
[2] Jiang S Z, Ye D P, Huang J Q, et al. Smart steganography:light-weight generative audio steganography model for smart embedding application[J]. Journal of Network and Computer Applications, 2020, 165(7):102689.
[3] Tirkel A Z, Rankin G A, Schynsel R V. Electronic watermark[C]//Digital Image Computing, Technology and Applications, 1993:666-673.
[4] Yang C H, Weng C Y, Wang S J. Adaptive data hiding in edge areas of images with spatial LSB domain systems[J]. IEEE Transactions on Information Forensics & Security, 2008, 3(3):488-497.
[5] Li Z, Chen X P, Pan X Z, et al. Lossless data hiding scheme based on adjacent pixel difference[C]//International Conference on Computer Engineering and Technology, 2009:588-592.
[6] Zhang X P, Wang S Z. Steganography using multiple-base notational system and human vision sensitivity[J]. IEEE Signal Process, 2005, 12(1):67-70.
[7] Huang F J, Huang J W, Shi Y Q. New channel selection rule for JPEG steganography[J]. IEEE Transactions on Information Forensics & Security, 2012, 7(4):1181-1191.
[8] Lin G S, Chang Y T, Lie W N. A framework of enhancing image steganography with picture quality optimization and anti-steganalysis based on simulated annealing algorithm[J]. IEEE Transactions on Multimedia, 2010, 12(5):345-357.
[9] Ruanaidh J K, Dowling W J, Boland F M. Phase watermarking for multimedia[J]. IEEE Transactions on Image Processing, 1997, 6(12):1673-1687.
[10] 许德合, 朱长青, 王奇胜. 利用DFT幅度和相位构建矢量空间数据水印模型[J]. 北京邮电大学学报, 2011, 34(5):25-28. Xu D H, Zhu C Q, Wang Q S. A construction of digital watermarking model for the vector geospatial data based on magnitude and phase of DFT[J]. Journal of Beijing University of Posts and Telecommunications, 2011, 34(5):25-28. (in Chinese)
[11] Kang Z W, Liu J, He Y G. Steganography based on wavelet transform and modulus function[J]. Journal of Systems Engineering and Electronics, 2007, 18(3):628-632.
[12] Hsieh M S, Tseng D C, Huang Y H. Hiding digital watermarks using multiresolution wavelet transform[J]. IEEE Transactions on Industrial Electronics, 2001, 48(5):875-882.
[13] Lin W H, Horng S J, Kao T W, et al. An efficient watermarking method based on significant difference of wavelet coefficient quantization[J]. IEEE Transactions on Multimedia, 2008, 10(5):746-757.
[14] Zhou Z L, Sun H, Harint R. Coverless image steganography without embedding[C]//Cloud Computing and Security. Springer, 2015:123-132.
[15] Zhang X, Peng F, Long M. Robust coverless image steganography based on DCT and LDA topic classification[J]. IEEE Transactions on Multimedia, 2018, 20(12):3223-3238.
[16] Yuan C S, Xia Z H, Sun X M. Coverless image steganography based on SIFT and BOF[J]. Journal of Internet Technology, 2017, 18:435-442.
[17] Otori H, Kuriyama S. Texture synthesis for mobile data communications[J]. IEEE Conference Graphics Applications, 2009, 29(6):74-81.
[18] Otori H, Kuriyama S. Data-embeddable texture synthesis[C]//Proceedings of the 8th International Symposium on Smart Graphics, Kyoto, Japan, 2007:146-157.
[19] 潘琳, 钱振兴, 张新鹏. 基于构造纹理图像的数字隐写[J]. 应用科学学报, 2016, 34(5):625-632. Pan L, Qian Z X, Zhang X P. Steganography by constructing texture images[J]. Journal of Applied Sciences, 2016, 34(5):625-632. (in Chinese)
[20] 司广文, 秦川, 姚恒, 等. 基于纹理特征分类与合成的鲁棒无载体信息隐藏[J]. 应用科学学报, 2020, 38(3):441-454. Si G W, Qin C, Yao H, et al. Robust coverless data hiding based on texture classification and synthesis[J]. Journal of Applied Sciences, 2020, 38(3):441-454. (in Chinese)
[21] Ren S Q, He K M, Girshick R. Faster-RCNN:towards real-time object detection with region proposal networks[C]//International Conference on Neural Information Processing Systems, 2015, 39:91-99.
[22] 周志立, 曹燚, 孙星明. 基于图像bag-of-words模型的无载体信息隐藏[J]. 应用科学学报, 2016, 34(5):527-536. Zhou Z L, Cao Y, Sun X M. Coverless information hiding based on bag-of-words model of image[J]. Journal of Applied Sciences, 2016, 34(5):527-536. (in Chinese)
[23] Lowe D G. Distinctive image features from scale-invariant key-points[J]. International Journal of Computer Vision, 2004, 60(2):91-110.
[24] Zheng S, Wang L, Ling B H, et al. Coverless information hiding based on robust image hashing[C]//International Conference on Intelligent Computing, 2017:1536-1547.

Robust Coverless Information Hiding Based on Image Classification

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments

[1]	CHEN Qing, XIA Lanting, BU Ying. Robust Watermarking Algorithm Based on Two-Level Singular Value Decomposition [J]. Journal of Applied Sciences, 2020, 38(6): 966-975.
[2]	SI Guangwen, QIN Chuan, YAO Heng, HAN Yanfang, ZHANG Zhichao. Robust Coverless Data Hiding Based on Texture Classification and Synthesis [J]. Journal of Applied Sciences, 2020, 38(3): 441-454.
[3]	LU Caiwu, QI Fan, RUAN Shunling. Grade Determination of Fine Grain Ore Based on Depth Image Analysis [J]. Journal of Applied Sciences, 2019, 37(4): 490-500.
[4]	WANG Ran, NIU Shao-zhang, PING Xi-jian, ZHANG Tao, SANG Xiao-dan. Steganalysis of JPEG Images Based on Reducing Between-Class Scatter [J]. Journal of Applied Sciences, 2019, 37(1): 41-50.
[5]	HE Zhi-hong, QIN Chuan, ZHOU Qing. High-Capacity Reversible Data Hiding for Encrypted Images [J]. Journal of Applied Sciences, 2018, 36(4): 611-627.
[6]	LIU Ming-ming, ZHANG Min-qing, LIU Jia, GAO Pei-xian, ZHANG Ying-nan. Coverless Information Hiding Based on Generative Adversarial Networks [J]. Journal of Applied Sciences, 2018, 36(2): 371-382.
[7]	LU Hai, SHAO Li-ping. Coverless Test Paper Disguise Combined with Non-direct Transmission and Random Codebook [J]. Journal of Applied Sciences, 2018, 36(2): 331-346.
[8]	CHEN Long-sheng, WANG Qi. Prescribed Performance Nonlinear PID Control for Uncertain Continuous Systems [J]. Journal of Applied Sciences, 2017, 35(6): 786-796.
[9]	LI Xin-wei, XIA Xiu-zhen. Robust Image Hashing Based on Content Structure Diagram [J]. Journal of Applied Sciences, 2016, 34(6): 691-701.
[10]	ZHOU Zhi-li, CAO Yi, SUN Xing-ming. Coverless Information Hiding Based on Bag-of-Words Model of Image [J]. Journal of Applied Sciences, 2016, 34(5): 527-536.
[11]	JIANG Cui-ling, LIN Jia-jun. Robust Image Hashing Based on Genetic Algorithm and BP Network [J]. Journal of Applied Sciences, 2016, 34(5): 537-546.
[12]	ZHANG Chun-sen, FENG Chen-yi, CUI Wei-hong, ZHENG Yi-wei, SUN Zhi-wei. Remote Sensing Image Classification for NationalGeomatics Monitoring Based on ConditionalRandom Field [J]. Journal of Applied Sciences, 2016, 34(4): 397-404.
[13]	FANG Qiao-yun, LÜ Dong-hui, SUN Jiu-ai. Improved Triangle Mesh Method for Surface Reconstruction from Normal Field [J]. Journal of Applied Sciences, 2016, 34(2): 145-153.
[14]	QIAN Hua-ming1, GE Lei1,2, HUANG Wei1. An Improved Strong Tracking Filtering Algorithm [J]. Journal of Applied Sciences, 2015, 33(1): 32-40.
[15]	LIU Ri, SUN Xiu-xia, LI Da-dong, DONG Wen-han. Counteracting Crosswind Sliding Mode Control of Ultra-low Altitude Airdrop Based on Feedback Linearization [J]. Journal of Applied Sciences, 2014, 32(3): 311-318.