浏览全部资源
扫码关注微信
Received：09 April 2018，
Revised：2018-6-8，
Published：30 October 2018
移动端阅览
目的
2
现有水印算法大多是基于明文域的，很容易被入侵、窃取。为了保护用户隐私、提高安全性，本文提出了一种用于盗版追踪的基于格雷码加密域的可逆水印方法，该方法支持对密文直接操作。
方法
2
首先提出了基于格雷码的同态加密系统（HESGC），并以此加密载体图像；然后依据整数小波变换（IWT）和人类视觉系统（HVS）特性，将图像分区并合理分类；再依据新提出的算法完成嵌入、可逆恢复及提取工作；最后利用首次提出的水印追踪联合策略（JWT）来进行盗版追踪。
结果
2
为了验证本文方法，选取USC-SIPI图像库中的6幅经典图像作为标准测试图像，与其他可逆水印算法相比，本文方法具有更高的PSNR值，PSNR高达50 dB，而且SSIM值均为1，实现了可逆功能；本文新提出的HESGC将使原始载体图像膨胀为原来的8倍，故容量较大。理论上，本文最大容量为3.75 bit/像素，目前大多可逆水印算法的最大容量不足1 bit/像素；本文方法不仅实现了盗版追踪功能，而且能够抵抗一些常见的攻击，如随机噪声、中值滤波、图像平滑和JPEG编码、LZW编码和卷积模糊等。通过比较原始追踪证明与攻击后图像的追踪证明可知，相似度在1左右的即为盗版，其他非盗版的相似度都远远低于1，大部分在0.6左右。
结论
2
本文提出了一种基于密文域的可逆水印方案，首次提出了HESGC和JWT，实现了密文域可逆水印技术和盗版追踪功能。该方案直接采用灰度图像作为水印图像，解除了以往以二值图像作为水印图像，或者将灰度图像二值化后作为水印图像的限制，而且采用基于级联混沌技术提高了灰度水印图像的安全性。此外，本文成功消除了图像分区分类中纹理/平滑区域中的平滑/纹理孤岛，使分类结果更加准确、合理。实验结果表明，本方案不仅能够抵抗一些常见攻击，而且容量大、安全性高，很好地保护了用户隐私。本文实现了密文域可逆水印技术，适用于隐私保护要求高的医学、军事等领域。
Objective
2
The rapid evolution of cloud technology has provided users with convenience but still has security risks. Users' privacy (e.g.
personal photos
corporate user information
and electronic notes) will be exposed once the cloud data are inaccessible or corrupted. Owing to the existence of security vulnerabilities or internal staff illicit activity
data may be tampered
replaced
or distributed illegally. In such a case
protecting the user' privacy is crucial. Currently and in practice
protecting the users' privacy is achieved by watermarking technology
especially reversible watermarking technology. Reversible watermarking can not only extract data correctly but also completely restore the original carrier. This technique is used in the medical
military
and other fields. Therefore
reversible watermarking technology plays an important role in the privacy protection field. Most of the existing reversible watermarking algorithms are based on the plaintext domain
such that they can be easily pirated or tampered. Thus
we proposed a reversible watermarking scheme in the homomorphic encrypted domain on the basis of Gray code for piracy tracing to enhance security and protect privacy. The proposed scheme provides support for a direct operation in the homomorphic encrypted domain. The ultimate goal of the new proposed scheme in the encrypted domain is to protect the users' privacy.
Method
2
First
the "homomorphic encryption system based on Gray code" (HESGC) is proposed to encrypt the original carrier image. Gray code encryption converts the grayscale values of the original carrier image into binary values. Second
in accordance with integer homomorphic encryption
the binary values are converted into different decimal grayscale values. Subsequently
region division and classification can be reasonably performed in accordance with the "integer wavelet transform" and "human visual system" characteristics. Region division is used to avoid conflicts between watermarking and tracing proofs
and region classification fits well with human visual characteristics. Humans are sensitive to smooth regions and minimally sensitive to the textured regions. Moreover
neighboring quadratic optimization approach is presented to improve the concentration of the same regions and enhance the accuracy and reasonability of region classification. Third
we implement the proposed embedding
reversible recovery
and extraction operations. Finally
we present "joint watermarking and tracing" (JWT) strategy and utilize it to achieve piracy tracing. The JWT strategy can trace piracy and the first unauthorized person who illegally copies or distributes the image. This study uses the nonrepudiation of tracing proofs.
Result
2
Experiments on the commonly used image database (i.e.
USC-SIPI) are conducted. Six classical images from the USC-SIPI image database are selected for this experiment. The proposed algorithm has higher peak signal-to-noise ratio (PSNR) values than the existing reversible watermarking algorithms
and the PSNR value can reach 50 dB. In addition
the structural similarity index metric values of the original carrier
restored
original watermarking
and extracted watermarking images are all equal to 1. The proposed scheme achieves a reversible recovery. Furthermore
the proposed HESGC expands the original carrier image by eight times
thus increasing the capacity. Theoretically
the maximum capacity of the algorithm proposed in this study is 3.75 bit/pixel. Currently
the maximum capacity of most existing reversible watermarking algorithms is less than 1 bit/pixel. Moreover
the proposed scheme can not only achieve piracy tracing but also resist several common attacks
such as random noise
median filter
image smoothing
JPEG-coded
LZW-coded
and convolutional fuzzy attacks. We calculate the similarity value of the extracted and generated tracing proofs by the image copyright owner and determine who has the maximum similarity value to identify the piracy origin. If the similarity value is approximately 1
then it is a pirate. For other non-pirates
the similarity value is less than 1
most of which are approximately 0.6. Experimental results confirm the efficiency of the proposed scheme.
Conclusion
2
In this study
we present the HESGC and JWT for the first time to achieve piracy tracing and reversible watermarking in an encrypted image. Most of the existing reversible watermarking algorithms directly use a binary sequence as the watermark. Alternatively
the gray image in this scheme serves as the watermark image directly; the restrictions when the binary image is used as the watermark image are removed
or the gray image is binarized as the watermark image. Moreover
cascade chaotic technology is adopted to encrypt the gray watermark image to enhance its security. We also successfully eliminate the smooth/textured islands in the textured/smooth regions
such that the block classification results are accurate and reasonable. In particular
security is an important measurement indicator for privacy protection
where only a secure watermarking system is meaningful. This study examines a triple security protection mechanism
which has the strongest security performance. The experimental results indicate that this scheme not only achieves privacy protection and piracy tracing but also has the characteristics of high security
large capacity
and high restoration quality. Moreover
this scheme can resist several common attacks
which are suitable for protecting users' privacy. The proposed algorithm focuses on the reversible watermarking technology in an encrypted image and is widely applied to digital images
such as military images
medical images
electronic invoice
and legal documents
that require high confidentiality
security
and fidelity.
Gibson J, Rondeau R, Eveleigh D, et al. Benefits and challenges of three cloud computing service models[C]//Proceedings of the 4th International Conference on Computational Aspects of Social Networks. Sao Carlos, Brazil: IEEE, 2012: 198-205.[ DOI:10.1109/CASoN.2012.6412402 http://dx.doi.org/10.1109/CASoN.2012.6412402 ]
Feng D G, Zhang M, Li H. Big data security and privacy protection[J]. Chinese Journal of Computers, 2014, 37(1):246-258.
冯登国, 张敏, 李昊.大数据安全与隐私保护[J].计算机学报, 2014, 37(1):246-258. [DOI:10.3724/SP.J.1016.2014.00246]
Thayananthan V, Albeshri A. Big data security issues based on quantum cryptography and privacy with authentication for mobile data center[J]. Procedia Computer Science, 2015, 50:149-156.[DOI:10.1016/j.procs.2015.04.077]
Saraladevi B, Pazhaniraja N, Paul P V, et al. Big data and Hadoop-a study in security perspective[J]. Procedia Computer Science, 2015, 50:596-601.[DOI:10.1016/j.procs.2015.04.091]
Bouslimi D, Coatrieux G, Quantin C, et al. A teleassistance protocol based on joint watermarking-encryption evidence for identification of liabilities in case of litigation[J]. IRBM, 2015, 36(5):279-286.[DOI:10.1016/j.irbm.2015.07.005]
Yin Z X, Abel A, Tang J, et al. Reversible data hiding in encrypted images based on multi-level encryption and block histogram modification[J]. Multimedia Tools and Applications, 2017, 76(3):3899-3920.[DOI:10.1007/s11042-016-4049-z]
Wang X F, Han X, Xi J H, et al. Reversible data hiding in encrypted image with separable data extraction from image decryption[J]. Multimedia Tools and Applications, 2017, 76(5):6127-6142.[DOI:10.1007/s11042-016-3288-3]
Di F Q, Duan J Y, Zhang M Q, et al. Encrypted image-based reversible data hiding with public key cryptography from interpolation-error expansion[C]//Proceedings of the 5th International Conference on Emerging Internetworking on Advances in Internetworking, Data & Web Technologies. Wuhan, China: Springer, 2017, 1: 138-149.[ DOI:10.1007/978-3-319-59463-7_14 http://dx.doi.org/10.1007/978-3-319-59463-7_14 ]
Shiu C W, Chen Y C, Hong W. Encrypted image-based reversible data hiding with public key cryptography from difference expansion[J]. Signal Processing:Image Communication, 2015, 39:226-233.[DOI:10.1016/j.image.2015.09.014]
Qian Z X, Zhang X P, Wang S Z. Reversible data hiding in encrypted JPEG bitstream[J]. IEEE Transactions on Multimedia, 2014, 16(5):1486-1491.[DOI:10.1109/TMM.2014.2316154]
Xiao D, Deng M M, Zhang Y S. Robust and separable watermarking algorithm in encrypted image based on compressive sensing[J]. Journal of Electronics&Information Technology, 2015, 37(5):1248-1254.
肖迪, 邓秘密, 张玉书.基于压缩感知的鲁棒可分离的密文域水印算法[J].电子与信息学报, 2015, 37(5):1248-1254.[DOI:10.11999/JEIT141017]
Bouslimi D, Coatrieux G. A crypto-watermarking system for ensuring reliability control and traceability of medical images[J]. Signal Processing:Image Communication, 2016, 47:160-169.[DOI:10.1016/j.image.2016.05.021]
Xiang S J, Luo X R, Shi S X. A novel reversible image watermarking algorithm in homomorphic encrypted domain[J]. Chinese Journal of Computers, 2016, 39(3):571-581.
项世军, 罗欣荣, 石书协.一种同态加密域图像可逆水印算法[J].计算机学报, 2016, 39(3):571-581. [DOI:10.11897/SP.J.1016.2016.00571]
Xiong L Z, Xu Z Q, Shi Y Q. An integer wavelet transform based scheme for reversible data hiding in encrypted images[J]. Multidimensional Systems and Signal Processing, 2018, 29(3):1191-1202.[DOI:10.1007/s11045-017-0497-5]
Dong J T, Li J B. A robust zero-watermarking algorithm for encrypted medical images in the DWT-DFT encrypted domain[M]//Chen W W, Tanaka S, Howlett R J, et al. Innovation in Medicine and Healthcare 2016. Cham: Springer, 2016: 197-208.[ DOI:10.1007/978-3-319-39687-3_19 http://dx.doi.org/10.1007/978-3-319-39687-3_19 ]
Xiao D, Chang Y T, Xiang T, et al. A watermarking algorithm in encrypted image based on compressive sensing with high quality image reconstruction and watermark performance[J]. Multimedia Tools and Applications, 2017, 76(7):9265-9296.[DOI:10.1007/s11042-016-3532-x]
Van Dijk M, Gentry C, Halevi S, et al. Fully homomorphic encryption over the integers[C]//Proceedings of the 29th Annual International Conference on the Theory and Applications of Cryptographic Techniques on Advances in Cryptology. French Rivie-ra: Springer, 2010, 6110: 24-43.[ DOI:10.1007/978-3-642-13190-5_2 http://dx.doi.org/10.1007/978-3-642-13190-5_2 ]
Liu M J, Wang A. Fully homomorphic encryption and its applications[J]. Journal of Computer Research and Development, 2014, 21(12):2593-2603.
刘明洁, 王安.全同态加密研究动态及其应用概述[J].计算机研究与发展, 2014, 21(12):2593-2603. [DOI:10.7544/issn1000-1239.2014.20131168]
Zhao F, Yao L S. Gray image encryption algorithm based on cascade chaostic[J]. Journal of Huaibei Normal University:Natural Science, 2017, 38(4):33-37.
赵凤, 姚丽莎.基于级联混沌的灰度图像加密算法[J].淮北师范大学学报:自然科学版, 2017, 38(4):33-37.
Wang G Y, Yuan F. Cascade chaos and its dynamic characteristics[J]. Acta Physica Sinica, 2013, 62(2):103-112.[
王光义, 袁方.级联混沌及其动力学特性研究[J].物理学报, 2013, 62(2):103-112.][DOI:10.7498/aps.62.020506]
Mallat S G. A theory for multiresolution signal decomposition:The wavelet representation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1989, 11(7):674-693.[DOI:10.1109/34.192463]
Nasr D B, Bahig H M, Daoud S S. Visualizing secure hash algorithm (SHA-1) on the web[C]//Proceedings of the 7th International Conference on Active Media Technology. Lanzhou, China: ACM, 2011: 101-112.
Arsalan M, Malik S A, Khan A. Intelligent reversible watermarking in integer wavelet domain for medical images[J]. Journal of Systems and Software, 2012, 85(4):883-894.[DOI:10.1016/j.jss.2011.11.005]
Al-Qershi O M, Khoo B E. Two-dimensional difference expansion (2D-DE) scheme with a characteristics-based threshold[J]. Signal Processing, 2013, 93(1):154-162.[DOI:10.1016/j.sigpro.2012.07.012]
Lei B Y, Tan E L, Chen S P, et al. Reversible watermarking scheme for medical image based on differential evolution[J]. Expert Systems with Applications, 2014, 41(7):3178-3188.[DOI:10.1016/j.eswa.2013.11.019]
Qiu Q, Ma X H. Reversible grayscale watermarking using integer wavelet transform and multi-objective genetic algorithm[J]. Journal of Computer-Aided Design&Computer Graphics, 2015, 27(7):1290-1297.
邱群, 马小虎.采用整数小波变换和多目标遗传算法的可逆灰度水印[J].计算机辅助设计与图形学学报, 2015, 27(7):1290-1297. [DOI:10.3969/j.issn.1003-9775.2015.07.019]
Parah S A, Ahad F, Sheikh J A, et al. A new reversible and high capacity data hiding technique for E-healthcare applications[J]. Multimedia Tools and Applications, 2017, 76(3):3943-3975.[DOI:10.1007/s11042-016-4196-2]
Yin Z X, Niu X J, Zhang X P, et al. Reversible data hiding in encrypted AMBTC images[J]. Multimedia Tools&Applications, 2018, 77:18067-18083.[DOI:10.1007/s11042-017-4957-6]
Zhang X P. Separable reversible data hiding in encrypted image[J]. IEEE Transactions on Information Forensics and Security, 2012, 7(2):826-832.[DOI:10.1109/TIFS.2011.2176120]
相关文章
相关作者
相关机构
京公网安备11010802024621
