Securing Transmitted Color Images Using Zero Watermarking and Advanced Encryption Standard on Raspberry Pi

Image authentication techniques have recently received a lot of attention for protecting images against unauthorized access.Due to the wide use of the Internet nowadays,the need to ensure data integrity and authentication increases.Many techniques,such as watermarking and encryption,are used for securing images transmitted via the Internet.The majority of watermarking systems are PC-based,but they are not very portable.Hardwarebased watermarking methods need to be developed to accommodate real-time applications and provide portability.This paper presents hybrid data security techniques using a zero watermarking method to provide copyright protection for the transmitted color images using multi-channel orthogonal Legendre Fourier moments of fractional orders(MFrLFMs)and the advanced encryption standard(AES)algorithm on a low-cost Raspberry Pi.In order to increase embedding robustness,the watermark picture is scrambled using the Arnold method.Zero watermarking is implemented on the Raspberry Pi to produce a real-time ownership verification key.Before sending the ownership verification key and the original image to the monitoring station,we can encrypt the transmitted data with AES for additional security and hide any viewable information.The receiver next verifies the received image’s integrity to confirm its authenticity and that it has not been tampered with.We assessed the suggested algorithm’s resistance to many attacks.The suggested algorithm provides a reasonable degree of robustness while still being perceptible.The proposed method provides improved bit error rate(BER)and normalized correlation(NC)values compared to previous zero watermarking approaches.AES performance analysis is performed to demonstrate its effectiveness.Using a 256×256 image size,it takes only 2 s to apply the zero-watermark algorithm on the Raspberry Pi.

A Image Copyright Protection Method Using Zero-Watermark by Blockchain and IPFS

Behind the popularity of multimedia technology,the dispute over image copyright is getting worse.In the digital watermark prevention technology for copyright infringement,watermark technology is considered to be an important technology to overcome data protection problems and verify the relationship between data ownership.Among the many digital watermarking technologies,zero watermarking technology has been favored in recent years.However,the existing zero watermark technology in the implementation process often needs a trusted third party to store watermarks,which may make the data too central,data storage security is low and copyright registration costs are too high,which creates a rare problem.The decentivization and information cannot be tampered of blockchain technology’s nature find new methods for image copyright protection.This paper studies the role of zero watermark algorithm in the image copyright and its complete storage and certification scheme,proposes a zero watermark image protection framework based on blockchain,and builds a system according to the framework.Combined with blockchain and zero watermarking technology,the framework uses inter IPFS(Inter Planetary File System)to solve the problem of blockchain efficient storage and sharing of large files.In addition,the application of user copyright information,image image query and image trading in the system are realized based on smart contracts,which solves the problem of lack of trusted third parties.Experiments show that the scheme is feasible and robust to various attacks.

ROBUST ZERO-WATERMARK ALGORITHMS BASED ON NUMERICAL RELATIONSHIP BETWEEN ADJACENT BLOCKS

In this paper, three robust zero-watermark algorithms named Direct Current coefficient RElationship (DC-RE), CUmulant combined Singular Value Decomposition (CU-SVD), and CUmulant combined Singular Value Decomposition RElationship (CU-SVD-RE) are proposed. The algorithm DC-RE gets the feature vector from the relationship of DC coefficients between adjacent blocks, CU-SVD gets the feature vector from the singular value of third-order cumulants, while CU-SVD-RE combines the essence of the first two algorithms. Specially, CU-SVD-RE gets the feature vector from the relationship between singular values of third-order cumulants. Being a cross-over studying field of watermarking and cryptography, the zero-watermark algorithms are robust without modifying the carrier. Numerical simulation obviously shows that, under geometric attacks, the performance of CU-SVD-RE and DC-RE algorithm are better and all three proposed algorithms are robust to various attacks, such as median filter, salt and pepper noise, and Gaussian low-pass filter attacks.

Robust Multi-Watermarking Algorithm for Medical Images Based on GoogLeNet and Henon Map

The field of medical images has been rapidly evolving since the advent of the digital medical information era.However,medical data is susceptible to leaks and hacks during transmission.This paper proposed a robust multi-watermarking algorithm for medical images based on GoogLeNet transfer learning to protect the privacy of patient data during transmission and storage,as well as to increase the resistance to geometric attacks and the capacity of embedded watermarks of watermarking algorithms.First,a pre-trained GoogLeNet network is used in this paper,based on which the parameters of several previous layers of the network are fixed and the network is fine-tuned for the constructed medical dataset,so that the pre-trained network can further learn the deep convolutional features in the medical dataset,and then the trained network is used to extract the stable feature vectors of medical images.Then,a two-dimensional Henon chaos encryption technique,which is more sensitive to initial values,is used to encrypt multiple different types of watermarked private information.Finally,the feature vector of the image is logically operated with the encrypted multiple watermark information,and the obtained key is stored in a third party,thus achieving zero watermark embedding and blind extraction.The experimental results confirmthe robustness of the algorithm from the perspective ofmultiple types of watermarks,while also demonstrating the successful embedding ofmultiple watermarks for medical images,and show that the algorithm is more resistant to geometric attacks than some conventional watermarking algorithms.

Robust Watermarking Algorithm for Medical Images Based on Non-Subsampled Shearlet Transform and Schur Decomposition

With the development of digitalization in healthcare,more and more information is delivered and stored in digital form,facilitating people’s lives significantly.In the meanwhile,privacy leakage and security issues come along with it.Zero watermarking can solve this problem well.To protect the security of medical information and improve the algorithm’s robustness,this paper proposes a robust watermarking algorithm for medical images based on Non-Subsampled Shearlet Transform(NSST)and Schur decomposition.Firstly,the low-frequency subband image of the original medical image is obtained by NSST and chunked.Secondly,the Schur decomposition of low-frequency blocks to get stable values,extracting the maximum absolute value of the diagonal elements of the upper triangle matrix after the Schur decom-position of each low-frequency block and constructing the transition matrix from it.Then,the mean of the matrix is compared to each element’s value,creating a feature matrix by combining perceptual hashing,and selecting 32 bits as the feature sequence.Finally,the feature vector is exclusive OR(XOR)operated with the encrypted watermark information to get the zero watermark and complete registration with a third-party copyright certification center.Experimental data show that the Normalized Correlation(NC)values of watermarks extracted in random carrier medical images are above 0.5,with higher robustness than traditional algorithms,especially against geometric attacks and achieve watermark information invisibility without altering the carrier medical image.

Robust Watermarking Algorithm for Medical Volume Data Based on Polar Cosine Transform and 3D-DCT

The amount of 3D data stored and transmitted in the Internet of Medical Things(IoMT)is increasing,making protecting these medical data increasingly prominent.However,there are relatively few researches on 3D data watermarking.Moreover,due to the particularity of medical data,strict data quality should be considered while protecting data security.To solve the problem,in the field of medical volume data,we proposed a robust watermarking algorithm based on Polar Cosine Transform and 3D-Discrete Cosine Transform(PCT and 3D-DCT).Each slice of the volume data was transformed by PCT to obtain feature row vector,and then the reshaped three-dimensional feature matrix was transformed by 3D-DCT.Based on the contour information of the volume data and the detail information of the inner slice,the visual feature vector was obtained by applying the per-ceptual hash.In addition,the watermark was encrypted by a multi-sensitive initial value Sine and Piecewise linear chaotic Mapping(SPM)system,and embedded as a zero watermark.The key was stored in a third party.Under the same experimental conditions,when the volume data is rotated by 80 degrees,cut 25%along the Z axis,and the JPEG compression quality is 1%,the Normalized Correlation Coefficient(NC)of the extracted watermark is 0.80,0.89,and 1.00 respectively,which are significantly higher than the comparison algorithm.

基于四元数分数阶广义拉盖尔图像矩的空间域零水印算法

现有的基于空间域零水印算法缺乏图像内容信息丢失检测的能力,特别是当图像遭受大面积裁切、随机涂抹或图像行列移除等攻击,水印提取算法就会失效。为了提高零水印算法抵抗图像遭受大面积裁切攻击的鲁棒性,提出一种基于四元数分数阶广义拉盖尔图像矩的空间域零水印算法。首先介绍分数阶广义拉盖尔多项式,其次构建四元数分数阶广义拉盖尔矩及不变量,最后设计彩色图像零水印算法。实验结果证明,所提出的零水印算法对常见的几何变换攻击具有一定的鲁棒性,同时对于滤波、有损压缩,特别是对图像大尺度剪切攻击具有较好的检测能力。

Research on secure buyer-seller watermarking protocol

A new buyer-seller watermarking protocol is proposed by applying a double encryption method and a novel mechanism of embedding a buyer＇s watermark. The protocol can effectively prevent against collusion attacks and the man in the middle attack if the third party is not trusted. Also, based on the proposed scheme for the first-hand transaction, a new buyer-reseller watermarking protocol and a formal multi-party watermarking protocol are also proposed. The proposed buyer-resell watermarking protocol only needs the original seller to provide transfer certificate and encryption-decryption service to support the second-hand transaction, and the multi-party watermarking protocol with distributed certificate authorities can overcome the difficulty in the combination of multicast mechanism with multiple unique watermarks and allow a seller to multicast the watermarked digital contents and key transaction information to n buyers. Furthermore, the idea of zero knowledge proof is also applied into the proposed scheme to allow the seller to take an effective control on the task performed by the third party.

基于以太坊的服装设计版权方案

现有的中心化服装设计版权体系中,低质量抄袭作品层出不穷,而作品的审核周期长且完成度不是非常高的阶段性成果又无法得到认可,使得创作者维权时往往缺乏这一时间段的时间证明。此外,作品的版权确权并不简洁,不利于版权的使用,数据本身也有遭受攻击的风险。为解决上述问题,提出了一个基于区块链、零水印和星际文件系统(IPFS)的服装设计版权方案。区块链的不可篡改特性保证了数据安全,使得其与传统版权保护流程能够有效结合。同时将区块链取代以往零水印中的可信知识产权保护(IPR)中央权威机构,消除了第三方带来的隐患。智能合约结合时间戳功能可以准确提供各步骤的线上记录,让创作者能更好提供作品从草稿到成品的时间线证明,以便在版权纠纷中维护自身权益。而感知哈希也能剔除掉抄袭作品,从抄袭作品的登记源头来控制低级抄袭作品的出现,保证创作者的著作权。实验表明,整体功能完善、安全性高,其中零水印方案具备可行性和有效性,作品登记和查询消耗的以太坊资源Gas成本低。

基于双混沌映射的遥感图像零水印算法

现有遥感图像零水印算法多为特定类型的遥感图像设计,普适性较差,且对水印组合攻击的鲁棒性不强。该文提出一种基于双混沌映射的遥感图像零水印算法。①对遥感图像进行非下采样剪切波变换,选取低频图像进行离散余弦变换;②对变换后的图像进行分块,并对各子块进行Schur分解,通过比较每个子块上三角矩阵中第一个元素值和均值的大小构建特征矩阵;③利用一维Logistic映射置乱遥感图像,与特征矩阵进行异或运算得到一个二值序列;①结合2D-LALM-Tent映射和Arnold置乱水印图像,对前述二值序列和置乱后水印的二值序列进行异或运算得到零水印。实验表明,该算法对不同类型遥感图像的适用性较好,且对水印组合攻击的鲁棒性较强,无精度损失,可用于多种类型遥感图像的版权保护,为遥感图像的共享提供安全保障。

基于ResNet50模型的矢量地图零水印算法

针对传统矢量地图零水印算法存在的抗几何攻击和要素增删攻击能力不足等问题,该文提出一种基于ResNet50模型的矢量地图零水印算法,在不改变矢量地图数据的情况下保护地图版权。该算法通过采用道格拉斯—普克算法提取矢量地图的复杂特征信息,将坐标集合映射为适合ResNet50模型处理的序列,通过ResNet50模型自动提取矢量地图数据中的特征,以实现零水印的构建。选择西安市餐饮、村庄、乡镇村道矢量地图数据集作为实验数据进行算法验证,结果表明,该算法在抗几何攻击和要素增删攻击方面均表现出色,在无损版权保护方面具有广阔的应用前景。

基于NMF和Hu不变矩的遥感影像零水印算法

为满足遥感影像数据在遭受大幅裁剪(强裁剪)后仍能有效保护版权的需求,该文提出一种基于非负矩阵分解(Nonnegative Matrix Factorization,NMF)和Hu不变矩的零水印算法。首先将原始影像数据分解为系数矩阵和基矩阵,然后计算整体Hu矩不变量均值和分块不变量均值,将两者得到的特征值二值化后与版权信息进行异或操作以生成零水印。其中,系数矩阵及零水印需存入第三方机构,为版权验证奠定基础。在检测版权信息时,利用NMF可复原特性,从待检测数据中反算出原始数据,并提取零水印以进行版权信息比对。实验结果表明,该算法具有版权保护的唯一性和鲁棒性,尤其在抗强裁剪方面表现突出,显示出在遥感影像数据版权保护领域的应用价值。

运用特征不变量的高精地图零水印算法

高精地图作为车辆导航和自动驾驶的核心组成部分,具有精度高、包含敏感信息、成本高等特点,其安全和保密至关重要。数字水印作为信息安全领域的重要工具,可以为高精地图数据提供认证和保护,但目前缺少针对高精地图的水印算法。该文根据高精地图的特性,提出一种高精地图零水印算法:根据高精地图用于表示车道信息的参数三次曲线数量确定水印索引;利用两个车道信息节点中参数三次曲线数量的奇偶性是否相同确定水印信息;结合水印索引依照投票原则构建特征矩阵,与加密后的水印图像进行异或运算生成零水印。实验结果表明,该算法在受到较高程度的几何攻击、增删攻击后仍能提取到较完整的水印信息,具有良好的鲁棒性。

基于组合变换域的彩色图像大容量零水印算法

针对现有大多数彩色图像零水印方案中水印嵌入容量小且抗几何攻击鲁棒性能不佳等问题,提出一种基于组合变换域和位平面分解的大容量鲁棒零水印算法。对彩色载体图像的R、G、B通道分别进行快速有限剪切波变换(FFST),并对变换后的各低频子带进行非重叠分块置乱,将置乱后的各子带的分块离散余弦变换(DCT)系数用于构造四元数离散余弦变换(QDCT)系数矩阵;在每个QDCT系数矩阵中选取两个低频系数,利用其各个实部和虚部的符号极性构造8个二值鲁棒特征矩阵;将经过正交拉丁方置乱加密后的灰度水印图像按位分解,把位分解后的8个二值位平面分别与以上二值鲁棒特征矩阵进行异或并重组得到灰度级认证零水印。此外,在水印检测前,采用ORB算法对待认证图像进行几何校正。实验结果表明,所提算法水印嵌入容量和安全性高,且对于常规非几何攻击和几何攻击均具有较强的鲁棒性。

结合空域不变量的变换域零水印二次检测方案

利用变换域水印技术对诸如压缩、滤波等信号处理具有较好鲁棒性的优点,结合空域中对几何变换具有抵抗力的常量来构造与检测零水印。实验证明,方案对剪切、数模转换处理、滤波、噪声、JPEG压缩、旋转等图像处理具有较强的鲁棒性。

二维矢量数字地图的零水印算法

提出了一种新的二维矢量数字地图的零水印算法。该算法选择矢量地图的顶点作为重要特征,把地图按坐标进行平均分块并统计各个分块中的顶点个数,利用变换与加密构造出标志版权信息的水印图。由于该算法不对原始地图数据进行任何修改,这使得传统水印算法的稳健性、安全性和不可感知性之间的矛盾用这种特殊的方法得到了很好的解决。实验结果表明,该零水印算法能够抵抗多种常见的攻击,可以用来对矢量数字地图进行版权保护。

关系数据库零水印注册方案的研究

对关系数据库的零水印方案的注册过程进行了研究,构造了关系数据库零水印的注册模型;依据注册模型提出了一套零水印注册机制,并描述了注册算法;最后分析了本方案的特点。

一种基于混沌调制的零水印算法

数字水印是一种通过在数字媒体里嵌入秘密信息来保护知识产权的技术。由于在图像中嵌入数字水印后,会导致图像一定程度的失真,因此,近年来出现了一种新的零水印方法。针对数字水印的不可感知性和鲁棒性之间的矛盾问题,提出了一种基于混沌调制的图像零水印方法,即该方法是从原始图像或测试图像的小波变换系数中提取低频子带部分小波系数的特征作为水印,而所抽取的小波系数的位置则由混沌法随机生成。实验结果表明,此算法的不可觉察性很好,并对一些诸如中值滤波、JPEG压缩、附加高斯噪声、裁剪和旋转等各种图像处理攻击有较强的鲁棒性。该方法改变了传统的向原始图像中嵌入水印信息的做法,不仅其得到的水印图像是无失真的,而且在不知道混沌初值的情况下,不可能成功地提取特征水印。

基于超混沌的医学图像篡改定位零水印算法

针对医学图像面临恶意篡改、信息窃取和泄露等安全问题,提出了一种基于超混沌的医学图像篡改定位零水印算法。首先将原始载体图像的最低有效位LSB(Least Singificant Bit)置零,然后将其分成互不重叠的子块,计算每块的均值,利用块中每个像素值与块均值的大小关系构造特征矩阵,最后利用Arnold置乱后的特征矩阵与超混沌加密的二值水印进行异或运算来构造零水印;另外,如果图像遭到篡改,通过计算差值图像,则能精确定位篡改位置及篡改形状。实验结果表明,该方案不仅具有较好的安全性,而且达到良好的篡改检测和定位效果。

一种基于混沌阵列的鲁棒零水印算法

本文提出了一种基于混沌阵列的鲁棒零水印算法.它首先构造一个混沌阵列,然后利用该混沌阵列来在图像中寻找'嵌入1'位置,得到该位置的像素值的最高有效位,再通过和水印信息的比较结果来在混沌阵列中设置标志,构造出最终的水印阵列.实验表明,该水印方案具有良好的鲁棒性,能够抵抗剪切、加扰、旋转、滤波、缩放、JPEG压缩等常见的有意和无意攻击.