基于准三维变换的视频隐写算法

结合离散余弦变换(DCT)的能量压缩能力和离散小波变换(DWT)的多分辨率特性,提出一种基于准三维变换的视频隐写算法。该算法利用二维小波变换描述视频序列的帧内信息,通过一维离散余弦变换描述视频序列的帧间信息,从而有效利用视频序列的空间及时间冗余,将秘密信息嵌入在DCT系数的量化过程中,保证了视频序列的稳定性及秘密信息提取的准确性。实验结果表明,该算法具有较好的视觉不可见性与较高的嵌入容量,且可实现秘密信息的盲提取。     

Robust JPEG steganography based on DCT and SVD in nonsubsampled shearlet transform domain

Social media platform such as WeChat provides rich cover images for covert communication by steganography. However, in order to save band-width, storage space and make images load faster, the images often will be compressed, which makes the image steganography algorithms designed for lossless network channels unusable. Based on DCT and SVD in nonsubsampled shearlet transform domain, a robust JPEG steganography algorithm is proposed, which can resist image compression and correctly extract the embedded secret message from the compressed stego image. First, by combining the advantages of nonsubsampled shearlet transform, DCT and SVD, the construction method for robust embedding domain is proposed. Then, based on minimal distortion principle, the framework of the proposed robust JPEG steganography algorithm is given and the key steps are described in details. The experimental results show that the proposed JPEG steganography algorithm can achieve competitive robustness and anti-detection capability in contrast to the state-of-the-art robust steganography algorithms. Moreover, it can extract the secret message correctly even if the stego image is compressed by WeChat.

     

Optimal wavelet transform using Oppositional Grey Wolf Optimization for video steganography

Data hiding in video is a method used to hide secret information within the video which is useful for secure multimedia data communication. The main goal of any video steganographic system is to reduce distortion of video and to secure the embedded data. A novel approach of hiding data using Oppositional Grey Wolf Optimization (OGWO) is proposed to minimize distortion and to enhance security so as to get superior video quality. In this work, scene changes are used to identify the key frames to hide the secret data. The scene changes are detected using Discrete Cosine Transform (DCT). Once the key frames are detected, OGWO is used at this stage to select the optimal region to embed the secret data. Lastly, the optimal region for entrenching is construed to embed the secret data using Discrete Wavelet Transform (DWT). Then, the payload and video are normalized using Inverse DWT to boost the video quality. The performance of the proposed system is measured using Peak Signal to Noise Ratio (PSNR), Embedding Capacity and Normalized Correlation (NC). The comparison results show that the proposed method delivers more security and minimizes distortions for improved video quality.

     

Maximizing embedding capacity for speech steganography: a segment-growing approach

It has been proven that the higher the correlation level between samples in the time-domain of a digital signal, the stronger the energy com paction property in the Discrete Cosine Transform (DCT) domain. This paper aims to investigate the limits of the DCT energy compaction property in speech signals by segmenting the cover speech signal into correlated segments and hide in each segment. The Hiding process is performed using a hiding strategy in spired by the Amplitude Modulation (AM) technique. Due to segmentation, the homogeneity is expected to increase which causes the energy of the signal to be strongly compacted in a few critical DCT coefficients, and therefore, a substantial amount of insignificant DCT coefficients can be replaced with the secret data without sacrificing the quality of the signal. Experimental results have proven the effectiveness of the proposed scheme which outperforms other speech steganography techniques recently published in the literature.

     

结合失真函数的稀疏域图像隐写算法

稀疏域图像隐写利用稀疏表示在载体图像中嵌入秘密信息。提出设计稀疏域图像隐写的失真函数,通过选择使失真函数最小的修改方式进行秘密嵌入,从而减小秘密信息嵌入对载体的影响。实验结果表明,该算法可以在保持图像视觉效果的同时,更有效地抵抗现有的隐写分析算法。     

一种基于时空冗余统计不可见性的视频隐写分析方法

视频中的扩频嵌入和MSU隐写是两种典型的隐写方法,可抵抗压缩等多种攻击。为有效检测利用此方法嵌入的秘密信息,根据视频的时空冗余特性,提出了一种实时的视频隐写分析方法。用大小为L+1的滑行窗口获取视频帧估计值,并提取相应的DCT和马尔可夫特征,使用神经网络、支持向量机等多种分类方法对隐写视频进行检测。结果表明,根据DCT和马尔可夫特征来分析,检测率较高。将支持向量机和时、空冗余特性等应用于视频隐写分析,有很大前景。     

减小H.264帧间漂移失真的鲁棒性视频隐写算法

针对H.264/AVC （Advanced Video Coding）视频信息隐藏过程中产生的不可感知性、嵌入容量、鲁棒性三方面不平衡的问题,提出一种通过选取不同优先级顺序的DCT （Discrete Cosine Transform）系数集合实现嵌入,进而减少帧间漂移失真的信息隐藏算法.首先对秘密信息M进行卷积编码,得到编码后的信息,以此提高视频的鲁棒性;然后通过分析帧间漂移失真产生的原因,计算出不同DCT系数优先级顺序的分类集合,优先在失真小的系数集合中嵌入数据从而减小帧间漂移失真;最后根据预先定义的嵌入规则,将嵌入在所选择4×4亮度块的DCT系数集合中,提高嵌入容量.最终在解码端能够正确提取秘密信息同时恢复原始信息.实验结果表明,本文提出的算法能在很好的保证视频质量的前提下,增加视频的嵌入容量,提高鲁棒性.     

无损载体和鲁棒代价结合的JPEG图像鲁棒隐写

目的 传统隐写技术在实际社交网络信道上难以保护秘密信息的完整性。在社交网络中,图像往往经过有损压缩信道进行传输,从而导致隐蔽通信失效。为了保证经过压缩信道传输的载密图像鲁棒性,设计安全鲁棒的隐蔽通信技术具有实际应用价值。基于最小化图像信息损失,本文提出无损载体和鲁棒代价结合的JPEG图像鲁棒隐写。方法 首先,指出构造无损载体能有效维持隐写安全性和鲁棒性的平衡,对经过压缩信道前后的JPEG图像空域像素块进行差分,构造无损载体以确定鲁棒嵌入域;其次,通过对离散余弦变换（discrete cosine transform,DCT）系数进行“±1”操作,并计算空域信息在压缩传输前后的损失,设计衡量DCT系数抗压缩性能的鲁棒代价;同时,验证在低质量因子压缩信道下鲁棒代价更能区分DCT系数的鲁棒能力,最后,利用校验子格编码（syndrome-trellis code,STC）,结合无损载体和鲁棒代价对秘密信息进行嵌入。结果 实验在BossBase1.01图像库上进行对比实验,相比于传统JPEG隐写技术,构造无损载体作为嵌入域能有效地将信息平均提取错误率降低24.97%,图像的正确提取成功率提高了21.35%;在此基础上,鲁棒代价进一步将信息平均提取错误率降低1.05%,将图像的正确提取成功率提高16.12%,验证了本文方法显著提高了隐写抗压缩性能。与J-UNIWARD （JPEG universal wavelet relative distortion）、JCRISBE （JPEG compression resistant solution with BCH code）和AutoEncoder （autoencoder and adaptive BCH encoding）3种现有典型隐写方法相比,提出的方法信息平均提取错误率分别降低了95.78%、93.17%和87.38%,图像的正确提取成功率为另外3种隐写方法的86.69倍、30.74倍和4.13倍。图像视觉质量逼近传统隐写方法,并保持较好的抗检测性。结论 本文提出的抗低质量因子JPEG压缩鲁棒隐写方法,获得的中间图像在经过压缩信道后,具有较强的抗压缩性和抗检测性,并保持较高的图像质量。     

发送方可否认图像隐写

目的 图像隐写是指将秘密信息隐藏到载体图像中,生成含密图像并在公共信道中传输。隐写分析旨在识别图像中是否隐藏秘密信息。不论何种隐写方案,都会在一定程度上被隐写分析识破,从而导致胁迫攻击,即攻击者找到发送方或接收方,胁迫其提交经过验证的秘密信息。为了保护秘密信息的隐蔽通信,对抗胁迫攻击的可否认方案亟待研究。在密码学领域,为了对抗胁迫攻击,已经提出了可否认加密的概念及相关方案并受到关注与研究。而在隐写领域,有研究提出可否认隐写的概念并设计了接收方可否认隐写的框架,但没有发送方可否认隐写的相关研究。对此,本文讨论发送方可否认隐写。方法 设计方案的通用框架,并构造两个方案:基于可逆网络的发送方可否认图像隐藏方案和基于可否认加密的发送方可否认图像隐写方案。在发送方可否认隐写的框架下,发送方可使用虚假的秘密信息生成与攻击者手中相同的含密图像,以欺骗攻击者,逃脱胁迫攻击,保护真实的秘密信息。结果 实验结果表明,两个方案都是可行且有效的,与原始隐写方案相比,可否认方案达到了发送方可否认功能的同时,均不会显著降低含密图像的视觉质量(峰值信噪比(peak signal-to-noise ratio,PSN...     

Efficient and secure data hiding in video sequence with three layer security: an approach using chaos

The fast development of communication and technology has created new challenges to transfer data securely. The techniques widely used to secure the data are cryptography and steganography. This paper presents a video steganography method to secure the information to be transmitted. Information transmitted can be an image, audio, text or video. This article presents a new technique that embeds data in the spatial domain of the cover video frame. The method employs chaotic maps to generate Random Positions (RP) to hide the information bits, random numbers for selecting the frames at which the information to be hidden and confusion order to encrypt the cover frame. The video frame is first selected based on Frame Selection (FS) is encrypted by applying Confusion Order (CO) and then embedding is carried out on the random positions generated. After embedding, the decrypted cover frame is replaced in a video sequence for transmission. This method provides three-level security in extracting the hidden secret information and also 25% of embedding capacity. Experimental outcomes (PSNR and payload) confirm that the method is competent.

     

High payload image steganography scheme with minimum distortion based on distinction grade value method

Presently, the design and development of an effective image steganography system are facing several challenges including the low capacity, poor robustness and imperceptibility. To surmount such limitations, it is important to improve the capacity and security of the steganography system while maintaining a high signal-to-noise ratio (PSNR). Based on these factors, this study is aimed to design and develop a distinction grade value (DGV) method to effectively embed the secret data into a cover image for achieving a robust steganography scheme. The design and implementation of the proposed scheme involved three phases. First, a new encryption method called the shuffle the segments of secret message (SSSM) was incorporated with an enhanced Huffman compression algorithm to improve the text security and payload capacity of the scheme. Second, the Fibonacci-based image transformation decomposition method was used to extend the pixel’s bit from 8 to 12 for improving the robustness of the scheme. Third, an improved embedding method was utilized by integrating a random block/pixel selection with the DGV and implicit secret key generation for enhancing the imperceptibility of the scheme. The performance of the proposed scheme is assessed experimentally to determine the imperceptibility, security, robustness and capacity. The resistance of the proposed scheme is tested against the statistical, χ², Histogram and non-structural steganalysis detection attacks. The obtained PSNR values revealed the accomplishment of the higher imperceptibility and security by the proposed DGV scheme while maintaining higher capacity compared to the reported findings. In short, the proposed steganography scheme outperformed the commercially available data hiding schemes, thereby resolved the existing issues.

     

以H.264为载体的隐秘传输方法

提出了一种H.264视频在流媒体环境下的隐秘传输方法。该方法将秘密信息分段备份,用哈希函数置乱分段及备份的嵌入顺序,当秘密信息由于丢帧而损失时,用备份信息来恢复损失的秘密信息。数位信息隐藏算法将信息嵌在I帧的[4×4]子块亮度DCT系数,改变7个中频系数中1个奇偶性嵌入3比特信息。实验表明,该方法在一定丢包率下能有效恢复损失的秘密信息,适合于流媒体应用环境。     

Reversible hiding in DCT-based compressed images

This paper presents a lossless and reversible steganography scheme for hiding secret data in each block of quantized discrete cosine transformation (DCT) coefficients in JPEG images. In this scheme, the two successive zero coefficients of the medium-frequency components in each block are used to hide the secret data. Furthermore, the scheme modifies the quantization table to maintain the quality of the stego-image. Experimental results also confirm that the proposed scheme can provide expected acceptable image quality of stego-images and successfully achieve reversibility.     

Exponential fractional cat swarm optimization for video steganography

In this paper, an effective method named Exponential Fractional-Cat Swarm Optimization (Exponential Fractional-CSO) along with multi-objective cost function is proposed. The proposed method is designed by integrating the CSO with the fractional concept based on the Exponential parameters. Initially, an input video is selected from the database from which frames are generated. Key frames are chosen among the frames using the contourlet transform and Structural Similarity Index Measure (SSIM). Regions are formed on the selected key frames through the help of grid lines. Once the regions are formed, optimal regions are ascertained with the help of the proposed optimization algorithm along with multi-objective cost functions to hide the secret data. During the embedding process, the secret data is hidden in the optimal region using the lifting wavelet transform (LWT). The embedded video is then transmitted through the network to reach its intended receiver. The experimental results reveal that the proposed Exponential Fractional-CSO obtained a maximal correlation of 0.9931 by considering the frames, maximal Peak Signal-to-Noise Ratio (PSNR) of 89.70 dB and MSE of 0.00006 respectively. Hence, the proposed method shows greater effectiveness of hiding the secret data in the video sequence along with data security.

     

安全的MPEG压缩视频数字隐写算法

视频数字隐写具有隐藏容量大的优点,但是通常在获得隐藏容量的间时,却忽视了安全性.为了在二者之间取得平衡,利用纠错码信息隐藏的原理,提出了一种以压缩视频为载体的数字隐写算法.该算法在进行秘密信息嵌入时,采用了二次嵌入的策略,即首先将秘密信息嵌入到纠错码码字,然后将得到的载密纠错码码字嵌入到与不采用差分编码的系数相对应的行程幅度对的幅度值,同时采用比特率控制策略来减小信息嵌入前后的视频流长度变化.实验及分析表明,该算法的隐写结果不仅具有较好的视觉和统计上的不可感知性,而且满足密码学中的"Kerchhoff准则".此外,该算法在确保一定的嵌入容量的情况下,能够使视频流长度在信息嵌入前后保持近似不变.     

WAVELET-BASED STEGANOGRAPHY

Wavelets, which are used to separate data into different components, have many applications. Steganography, one such application, is a form of secret communication where the existence of a message is concealed. Methods for applying univariate and bivariate wavelets to steganography include embedding messages into the insignificant wavelet coefficients of decomposed signals and images. Recomposing then creates stego-objects that appear unaltered from the original cover-objects. First demonstrated is a technique for hiding messages in strings of data with linear trends using the univariate Daubechies D ₄ wavelets. Then, after developing the bivariate Haar wavelets and filters, a unique process of decomposing and recomposing an image in greyscale in order to implement steganography will be illustrated.     

Wavelet domain-based video noise reduction using temporal discrete cosine transform and hierarchically adapted thresholding

A novel spatio-temporal filter for video denoising, which operates entirely in the wavelet domain, is proposed. For effective noise reduction, the spatial and temporal redundancies that exist in the wavelet domain representation of a video signal are exploited. First, a 2D discrete wavelet transform is applied to the input noisy frames. This is followed by a discrete cosine transform (DCT), which is applied to the temporal subband coefficients to minimise the redundancy among the consecutive frames. The DCT transformed, noise-free coefficients in the different wavelet domain subbands for the original image sequence are modelled using a prior having a generalised Gaussian distribution. On the basis of this prior, filtering of the noisy wavelet coefficients in each subband is carried out using a new, low-complexity wavelet shrinkage method, which utilises the correlation that exists between subsequent resolution levels. Experimental results show that the proposed scheme outperforms several state-of-the-art spatio-temporal filters in terms of both the peak signal-to-noise ratio and the visual quality     

Performance enhanced image steganography systems using transforms and optimization techniques

Image steganography is the art of hiding highly sensitive information onto the cover image. An ideal approach to image steganography must satisfy two factors: high quality of stego image and high embedding capacity. Conventionally, transform based techniques are widely preferred for these applications. The commonly used transforms for steganography applications are Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT) etc. In this work, frequency domain transforms such as Fresnelet Transform (FT) and Contourlet Transform (CT) are used for the data hiding process. The secret data is normally hidden in the coefficients of these transforms. However, data hiding in transform coefficients yield less accurate results since the coefficients used for data hiding are selected randomly. Hence, in this work, optimization techniques such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used for improving the performance of the steganography system. GA and PSO are used to find the best coefficients in order to hide the Quick Response (QR) coded secret data. This approach yields an average PSNR of 52.56 dB and an embedding capacity of 902,136 bits. These experimental results validate the practical feasibility of the proposed methodology for security applications.     

Steganalysis of stochastic modulation steganography

Steganography[1] conceals the occurrence and real purpose of communication by em- bedding message into the cover medium, such as an image, audio or video. Because im- age is widely used in Internet and has much redundancy, it has been one of the most im- …     

基于MME和IRB的信息隐写算法

为提高隐写算法的安全性,提出一种基于MME(modified matrix encoding)和IRB(iterative random blocking)的信息隐写算法。通过分析基于IRB的隐写算法流程,找到了其载密图像质量下降的主要原因,使用MME改进了该算法。实验结果表明,相比于IRB隐写算法,改进算法提高了载密图像质量,同时提高了抵抗盲检测的能力。改进算法表明了使用隐写编码可提高嵌入效率,从而提高隐写算法的安全性。