A Review of Image Steganography Based on Multiple Hashing Algorithm

Steganography is a technique for hiding secret messages while sending and receiving communications through a cover item.From ancient times to the present,the security of secret or vital information has always been a significant problem.The development of secure communication methods that keep recipient-only data transmissions secret has always been an area of interest.Therefore,several approaches,including steganography,have been developed by researchers over time to enable safe data transit.In this review,we have discussed image steganography based on Discrete Cosine Transform(DCT)algorithm,etc.We have also discussed image steganography based on multiple hashing algorithms like the Rivest–Shamir–Adleman(RSA)method,the Blowfish technique,and the hash-least significant bit(LSB)approach.In this review,a novel method of hiding information in images has been developed with minimal variance in image bits,making our method secure and effective.A cryptography mechanism was also used in this strategy.Before encoding the data and embedding it into a carry image,this review verifies that it has been encrypted.Usually,embedded text in photos conveys crucial signals about the content.This review employs hash table encryption on the message before hiding it within the picture to provide a more secure method of data transport.If the message is ever intercepted by a third party,there are several ways to stop this operation.A second level of security process implementation involves encrypting and decrypting steganography images using different hashing algorithms.

An Improved Image Steganography Security and Capacity Using Ant Colony Algorithm Optimization

This advanced paper presents a new approach to improving image steganography using the Ant Colony Optimization(ACO)algorithm.Image steganography,a technique of embedding hidden information in digital photographs,should ideally achieve the dual purposes of maximum data hiding and maintenance of the integrity of the cover media so that it is least suspect.The contemporary methods of steganography are at best a compromise between these two.In this paper,we present our approach,entitled Ant Colony Optimization(ACO)-Least Significant Bit(LSB),which attempts to optimize the capacity in steganographic embedding.The approach makes use of a grayscale cover image to hide the confidential data with an additional bit pair per byte,both for integrity verification and the file checksumof the secret data.This approach encodes confidential information into four pairs of bits and embeds it within uncompressed grayscale images.The ACO algorithm uses adaptive exploration to select some pixels,maximizing the capacity of data embedding whileminimizing the degradation of visual quality.Pheromone evaporation is introduced through iterations to avoid stagnation in solution refinement.The levels of pheromone are modified to reinforce successful pixel choices.Experimental results obtained through the ACO-LSB method reveal that it clearly improves image steganography capabilities by providing an increase of up to 30%in the embedding capacity compared with traditional approaches;the average Peak Signal to Noise Ratio(PSNR)is 40.5 dB with a Structural Index Similarity(SSIM)of 0.98.The approach also demonstrates very high resistance to detection,cutting down the rate by 20%.Implemented in MATLAB R2023a,the model was tested against one thousand publicly available grayscale images,thus providing robust evidence of its effectiveness.

Steganography Algorithm to Hide Secret Message inside an Image

In this paper, the authors propose a new algorithm to hide data inside image using steganography technique. The proposed algorithm uses binary codes and pixels inside an image. The zipped file is used before it is converted to binary codes to maximize the storage of data inside the image. By applying the proposed algorithm, a system called Steganography Imaging System （gig） is developed. The system is then tested to see the viability of the proposed algorithm. Various sizes of data are stored inside the images and the Peak signal-to-noise ratio （PSNR） is also captured for each of the images tested. Based on the PSNR value of each images, the stego image has a higher PSNR value. Hence this new steganography algorithm is very efficient to hide the data inside the image.

Optimizing Region of Interest Selection for Effective Embedding in Video Steganography Based on Genetic Algorithms

With the widespread use of the internet,there is an increasing need to ensure the security and privacy of transmitted data.This has led to an intensified focus on the study of video steganography,which is a technique that hides data within a video cover to avoid detection.The effectiveness of any steganography method depends on its ability to embed data without altering the original video’s quality while maintaining high efficiency.This paper proposes a new method to video steganography,which involves utilizing a Genetic Algorithm(GA)for identifying the Region of Interest(ROI)in the cover video.The ROI is the area in the video that is the most suitable for data embedding.The secret data is encrypted using the Advanced Encryption Standard(AES),which is a widely accepted encryption standard,before being embedded into the cover video,utilizing up to 10%of the cover video.This process ensures the security and confidentiality of the embedded data.The performance metrics for assessing the proposed method are the Peak Signalto-Noise Ratio(PSNR)and the encoding and decoding time.The results show that the proposed method has a high embedding capacity and efficiency,with a PSNR ranging between 64 and 75 dBs,which indicates that the embedded data is almost indistinguishable from the original video.Additionally,the method can encode and decode data quickly,making it efficient for real-time applications.

Steganography Using Reversible Texture Synthesis Based on Seeded Region Growing and LSB

Steganography technology has been widely used in data transmission with secret information.However,the existing steganography has the disadvantages of low hidden information capacity,poor visual effect of cover images,and is hard to guarantee security.To solve these problems,steganography using reversible texture synthesis based on seeded region growing and LSB is proposed.Secret information is embedded in the process of synthesizing texture image from the existing natural texture.Firstly,we refine the visual effect.Abnormality of synthetic texture cannot be fully prevented if no approach of controlling visual effect is applied in the process of generating synthetic texture.We use seeded region growing algorithm to ensure texture’s similar local appearance.Secondly,the size and capacity of image can be decreased by introducing the information segmentation,because the capacity of the secret information is proportional to the size of the synthetic texture.Thirdly,enhanced security is also a contribution in this research,because our method does not need to transmit parameters for secret information extraction.LSB is used to embed these parameters in the synthetic texture.

Steganography algorithm for adaptive multi-rate wideband speech based on algebraic codebook search

With the popularity of adaptive multi-rate wideband （AMR-WB） audio in mobile communication, many AMR- WB based techniques, such as a similar compression architecture to transmit secret information during the process of compression, were proposed to transmit covert messages. However, if a sender does not have the original waveform audio format （WAV） audio, the architecture cannot be used. In this paper, a new covert message method, which takes effect after WAV audio is compressed into AMR-WB speech, is proposed. This method takes advantage of algebraic codebook search. Aiming at improving speed and reducing search space, it does not perform algebraic codebook search using the optimal search algorithm, and it does not reach the positions of non-zero pulses via depth-first tree search that characterizes the energy of audio. According to the features of search methods and the codebook index construction, every track in each subframe is analyzed to find the proper positions for embedding secret information. Experimental results show that the proposed method has satisfactory capacity and simplicity regardless of compression process.

基于QR码和信息隐藏的秘密图像安全分享方案

随着数字化时代的到来,防止数据和信息的泄露问题是现如今持久关注的问题。在视觉密码加密过程中,人们侧重于原始秘密信息的保护,而忽视了对共享份保护以及信息传输过程中发送者与参与者的验证。因此,本文在(k,n)像素不扩展的视觉密码方案下,基于QR码的纠错容错功能,对现存的隐藏方法进行改进,提出了一种保护秘密共享份的安全分享方案。针对QR码在重要信息的传输时,易被窃取者任意读取篡改这一现实问题,利用RSA非对称加密算法对QR码的发送传输进行验证保护。实验结果表明,本文方案减少了共享份在加密和发送过程中受到的攻击性,实现了对发送者和参与者的验证,保证了QR码编码内容的真实性和传播过程中的可靠性。

基于拉格朗日分存的彩色图像隐写算法

为提高彩色数字图像隐写算法的安全性,提出一种基于拉格朗日分存原理的隐写算法。秘密图像在置乱之后被转换成二进制比特流,彩色载体图像根据RGB通道分解为3幅灰度图像,利用拉格朗日分存算法,每个通道的灰度图像先分存为3幅图像再合并成一幅图像,秘密信息在载体图像合并的过程中被嵌入到载体图像中,根据载体图像每个像素点分存之后的奇偶性进行秘密信息的嵌入。仿真结果表明,该隐写算法具有较高的抗裁剪性、安全性及隐秘性。

一种抗SPA分析的图像信息隐藏方法

通过分析SPA(sample pair analysis)算法的检测原理,提出了一种抗SPA分析的信息隐藏方法.该方法根据载体图像的统计特性,按计算的比例混合使用两种替换方法来嵌入信息,使得SPA算法的检测值趋于最小.实验结果表明,该方法在信息嵌入时可以调节载体图像的统计特性,不仅可以有效地抵抗SPA算法,而且对其他隐藏分析算法也很有效.

Memetic Optimization with Cryptographic Encryption for Secure Medical Data Transmission in IoT-Based Distributed Systems

In the healthcare system,the Internet of Things(IoT)based distributed systems play a vital role in transferring the medical-related documents and information among the organizations to reduce the replication in medical tests.This datum is sensitive,and hence security is a must in transforming the sensational contents.In this paper,an Evolutionary Algorithm,namely the Memetic Algorithm is used for encrypting the text messages.The encrypted information is then inserted into the medical images using Discrete Wavelet Transform 1 level and 2 levels.The reverse method of the Memetic Algorithm is implemented when extracting a hidden message from the encoded letter.To show its precision,equivalent to five RGB images and five Grayscale images are used to test the proposed algorithm.The results of the proposed algorithm were analyzed using statistical methods,and the proposed algorithm showed the importance of data transfer in healthcare systems in a stable environment.In the future,to embed the privacy-preserving of medical data,it can be extended with blockchain technology.

最优像素调整耦合基因算法的高容量图像隐写研究

针对当前图像隐写方案存在阶梯效应,使其不可感知能力差,且其信息隐藏容量小(≤50%)等不足,设计了最优像素调整耦合基因算法的高容量图像隐写术。基于HDWT(Hara discerte wavelet transform)机制,构造隐藏信息长度计算模型,找出图像分块的频域表示,以改善隐写鲁棒性;根据载体图像与隐写图像之间的绝对误差,设计适应度函数,借助基因算法,获取最优映射函数,将秘密信息嵌入到HDWT系数中;并设计最优像素变换方案,降低载秘图像与载体图像之间的嵌入误差,显著增大隐写容量;再设计其提取机制,获取信息图像;以PSNR(peak signal to ratio)构建反馈机制,优化提取质量。仿真结果显示,与其他隐写机制相比,该算法具备更大的隐写容量和更强的不可感知性能;拥有更高的检测精度,可有效区分载体与隐写图像特征值。

基于边缘计算的进化多目标优化图像隐写算法

边缘计算解决了终端因计算资源有限而不能运行复杂应用的弊端,在实际应用中可以支持计算资源受限的终端实现基于图像隐写的隐蔽通信.提出了一种适用于边缘计算场景的进化多目标优化图像隐写算法,首先将优化隐写不可察觉性和隐写安全性作为目标函数,给出了图像隐写的形式化定义;其次通过多个定向和非定向的高通滤波器对图像进行预处理,得到叠加的滤波残差作为秘密信息嵌入的候选位置;然后利用遗传算法中的基因操作,在候选位置中逐代寻找适应度高的个体以得到进化多目标优化问题的最优解;最后,在最优解对应的像素位置实现秘密信息的嵌入.通过和现有算法的仿真对比分析结果表明:提出的算法能够很好地保持图像质量,具有较好的抵抗隐写分析的能力.

基于国密算法的应用层协议隐写系统

针对机密信息的隐蔽安全传输问题,提出一种基于国密SM算法的应用层协议隐写系统。系统以国密SM算法为加密、认证基础,结合应用层协议隐写的特点,以框架式、插件化的设计思路,详细阐述系统的主要构成部分(发信端和收信端),构建系统总体架构,并进行系统测试。测试结果表明:该系统能够有效地对机密信息进行加密传输,实现了可扩展、多种协议并发的功能,具有一定的理论意义和实践价值。

PN序列估计与扩频隐藏信息分析

在非协作信息侦测情况下,提出了一种直接序列扩频(DS-SS)信号PN序列的估计方法,在此基础上实现了扩频隐藏信息的盲提取.该方法以估计序列和扩频信号的累积相关值为目标函数,建立估计序列长度及其构成的两变量优化模型,通过遗传算法求解,可较好地估计出PN序列.通过获取的PN序列与藏密信号的相关性分析,可实现扩频隐藏信息的盲提取.该方法已在微机上进行了实验,实验结果表明,该方法在截获信号信噪比较低情况下仍具有较好的估计性能,提取的秘密信息具有较好的可辨认性.

基于小波变换和Feistel密码结构的图像置乱技术

由于图像信息在网络进行传输时，很容易被非法截取，而隐写术能起到保护机密信息免受攻击的作用，因而得到了广泛的研究和应用。置乱技术虽然是隐写术的预处理过程，但它在隐写术中起着非常重要的作用。提出了一种新的基于小波变换和Feistel密码结构的图像置乱方法，其置乱的对象是载体图像中的小波系数，置乱算法基于Feistel密码结构，密钥采用变形约瑟夫遍历产生，属于“一次一密”的密钥生成。将该方法用于油料信息图像隐藏实验取得了良好的效果。

基于递进多目标蛙跳优化的LSB±K隐写算法

设计一种采用非支配排序、拥挤机制和种群重构等策略的递进多目标混合蛙跳算法,可有效保证Pareto前沿的多样性和均匀性.将该多目标优化算法用于设计LSB±K隐写算法.在优化过程中对图像分块,对应所有图像子块组成的矩阵构成优化算法的可行解,矩阵元素代表对应图像块像素的嵌入位数.以载体图像与载密图像差分图的直方图特征函数质心差和隐写容量为两个优化目标,对不同图像块的嵌入位数进行优化.实验结果表明,采用递进多目标混合蛙跳优化的LSB±K隐写算法,与相近抗分析性能下的LSBM隐写及单目标优化LSBM隐写相比,嵌入容量提高了30%;与相同容量的LSB±2隐写及单目标优化LSB±2隐写相比,抗分析能力更强.

遗传算法在图像DCT域中嵌入数字水印的应用

提出一种新颖的、鲁棒的隐写系统,采用遗传算法将水印信息嵌入到图像的DCT变换域中,实现水印信息的最优化嵌入。该算法提取出的水印无失真,可以改善水印系统不可感知性和不可统计性。实验结果表明,该方法抵抗噪声较强,但其平滑攻击、锐化攻击的能力较差。

基于PDF文档作为掩体的信息隐写方法

目前应用极为广泛的PDF文档,发现了其中存在可以用作信息隐写的隐密信道。通过采用以一定的冗余换取安全性的策略,并使用基于混沌模型的随机选择隐写单元的方法,使隐写系统满足Kerckhoffs原理。分析和实验结果表明,该文隐写方法可嵌入任意大小的信息,并保持在PDF阅读器中显示的透明性,具有较好的简单实用性。

基于CRITIC权与灰色关联的隐写分析算法综合评估

在基于灰色关联分析的隐写分析算法评估过程中,针对权值分配不合理的问题,采用标准间重要性相关性方法确定各指标的初始权重,结合决策情况对待主动修改的指标权重进行增减,并将这些增减的权重平均分配给被动变化的指标,从而实现对权重的调整,得到各指标的最终权值。运用灰色关联分析法计算各个待评价对象与最优序列之间的加权灰色关联度,并依据加权关联度的大小完成对隐写分析算法的评估。仿真结果表明,与其他隐写分析算法相比,该方法能更加有效地评估各类隐写分析算法的优劣。

基于Huffman编码的MP3隐写算法

针对MP3音频的编码特点,提出了基于Huffman码字替换原理的音频隐写算法。与以往的MP3隐写算法相比,该算法直接在MP3帧数据流中的Huffman码字上嵌入隐蔽信息,不需要局部解码,具有透明度高、嵌入量大、计算量小的特点。通过实验分析了算法的透明性、嵌入量、码字的统计特性等方面的特点。