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

摘要/Abstract

摘要： 针对传统信息隐藏方法须通过修改载体以嵌入秘密信息所带来的安全性问题,提出一种基于图像分类与尺度不变特征转换(scale-invariant feature transform,SIFT)提取无载体信息隐藏的方法。首先通过快速区域卷积神经网络将原始图像库进行分类处理,生成不同种类的子图像库;然后利用图像SIFT特征点的方向信息设计一个感知鲁棒的哈希方案,并使用该方案计算出每个子图像库中图像的哈希值,将所有子图像库中的图像全部映射成相应的二进制哈希值;最后将秘密信息分割成若干个片段,通过对比秘密信息片段与所有的图像二进制哈希值,从子图像库中检索出与秘密信息片段相符的图像,将其作为含密图像传送给接收方,完成信息隐藏过程。接收方接收到全部含密图像后,根据约定的哈希方案提取秘密信息。实验结果和分析表明,该方法对JPEG压缩、高斯噪声、椒盐噪声、图像缩放等攻击具有较强的鲁棒性,且隐藏容量较高。

关键词: 无载体信息隐藏, 图像分类, 图像哈希, 鲁棒性, 隐藏容量

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

中图分类号:

TP309

董腾林, 李欣然, 姚恒, 秦川. 基于图像分类的鲁棒无载体信息隐藏[J]. 应用科学学报, 2021, 39(6): 893-905.

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.

参考文献

[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.