Secure steganography based on binary particle swarm optimization

The objective of steganography is to hide message securely in cover objects for secret communication. How to design a secure steganographic algorithm is still major challenge in this research field. In this letter, developing secure steganography is formulated as solving a constrained IP (Integer Programming) problem, which takes the relative entropy of cover and stego distributions as the objective function. Furthermore, a novel method is introduced based on BPSO (Binary Particle Swarm Optimization) for achieving the optimal solution of this programming problem. Experimental results show that the proposed method can achieve excellent performance on preserving neighboring co-occurrence features for JPEG steganography.     

Region based Image Steganalysis using Artificial Bee Colony

Steganalysis is the art and skill of discriminating stego images from cover images. Image steganalysis algorithms can be divided into two broad categories, specific and universal. In this paper, a novel universal image steganalysis algorithm is proposed which is called RISAB, Region based Image Steganalysis using Artificial Bee colony. The goal of the proposed method is to realize a sub-image from stego and cover images through ABC with respect to density according to the cover, stego and difference images. In our method, we look for the best sub-image, which contains the highest density with respect to the changed embedding pixels. Furthermore, after selecting the best sub-image, we extract the features, which have been selected by IFAB, Image steganalysis based on Feature selection using Artificial Bee colony. At the end, both selected features by IFAB and extracted features by RISAB are combined. As a result, a feature vector is generated which improves accuracy of steganalysis. Experimental results show that our proposed method outperforms other approaches.     

Invertible secret image sharing scheme based on improved FEMD

Based on the improved FEMD algorithm an invertible secret image sharing scheme was proposed.Firstly,the embedding process of secret data was improved to make the original pixel pair and the stego pixel-pair to become a one-to-one mapping.Then a unique status flag was set to be calculated to record and process the original status of the over flow pixel-pair.Experimental data and analysis show that the proposed algorithm can guarantee the generation of high quality cryptographic images and solve the problem that the original carrier image can not be restored.     

基于编码压缩和加密的图像可逆信息隐藏算法

提出一种编码压缩和加密的图像可逆信息隐藏算 法。计算载体像素预测值与其像素值的差值, 对差值进行哈夫曼编码压缩,通过压缩数据和随机数据加密重构图像,得到载体数据。将哈 夫曼编码的码 表和秘密信息隐藏在载体数据中,实现信息隐藏。在载密数据中提取码表数据和秘密信息, 对加密压缩数 据进行解密,结合码表和预测方法恢复原始图像。实验结果表明,本文算法具有较大的隐藏 容量,不仅能 正确提取秘密信息,还能无损恢复原始图像。     

一种基于DCT域统计特征的JPEG图像隐写分析

提出了一种基于DCT域统计特征的JPEG图像隐写分析算法。该算法在分析JPEG图像的DCT域统计特性的基础上,提取了8维特征向量,通过LSSVM分类器对待测图像进行分类,以达到检测载密图像的目的。算法实现简单、计算复杂度低。实验结果表明,该算法检测速度快,具有较高的检测正确率,能够实现针对各类JPEG图像信息隐藏算法的有效检测。     

）istortion-Free Data Embedding Scheme for Hig Dynamic Range Images

Distortion-free data embedding is a technique which can assure that not only the secret data is correctly extracted but also the cover media is recovered without any distortion after secret data is extracted completely. Because of these advantages, this technique attracts the attention of many researchers. In this paper, a new distortion-free data embedding scheme for high dynamic range (HDR) images is proposed. By depending on Cartesian product, this scheme can obtain higher embedding capacity while maintaining the exactly identical cover image and stego image when using the tone mapping algorithms. In experimental results, the proposed scheme is superior to Yu et al.'s scheme in regard to the embedding rate-an average embedding rate of 0.1355 bpp compared with Yu et al.'s scheme (0.1270 bpp).     

一种针对JPEG图像的通用隐写分析算法

提出了一种针对JPEG图像的通用隐写分析算法。该算法提取了15个具有良好分类特性的特征参数,输入构建的KS—SVM分类器．以达到检测载密图像的目的。实验结果表明,该算法的检测正确率较高,检测速度快,能够实现针对各类JPEG载密图像的有效检测。     

n维超立方体模映射安全隐写算法

针对目前基于模函数的隐写研究现状,提出n维超立方体模映射隐写算法.根据模运算性质定义一个n维模函数,将n个像素值映射到一位aⁿ进制数值,从而可以实现将一位aⁿ进制信息隐藏到n个像素中.选择不同的参数a可以得到不同的嵌入率和载密图像视觉质量,选择较大的参数n且a为偶数时可以得到更好的载密图像视觉质量.理论分析和实验结果表明,本文算法与众多隐写算法相比,不仅具备这些算法的功能,而且具有更好的载密图像视觉质量、安全性和更强的实用性.     

New framework for unsupervised universal steganalysis via SRISP-aided outlier detection

Formulating steganalysis as a binary classification problem has been highly successful. However, the existing detection algorithms are difficult to obtain high detection accuracy when applied in real-world circumstances. Because so-called model mismatch problem often occurs owing to unknown cover source and embedding parameters. To avoid the mess of model mismatch, we propose a new unsupervised universal steganalysis framework to detect individual stego images. First, cover images with statistical properties similar to those of the given test image are searched from a retrieval cover database to establish an aided cover sample set. Second, unsupervised outlier detection is performed on a test set composed of the given test image and its aided cover sample set to determine the type (cover or stego) of the given test image. Our proposed framework, called Similarity Retrieval of Image Statistical Properties (SRISP)-aided unsupervised outlier detection, requires no training, and thus it does not suffer from model mismatch. The framework employs standard steganalysis features and detects each test image individually. Experimental results illustrate that the framework substantially outperforms one-class support vector machine and the traditional unsupervised outlier detectors without considering SRISP; its detection performance is independent of the proportion of stego images in the test samples.     

基于条件概率的MFP量化隐藏的隐写分析算法

MFP隐藏方法将小波变换后的中频系数对分为重要系数与不重要系数,用不同的算法嵌入隐藏信息,且对原图像的小波分解的各子带系数的直方图统计特性影响并不明显。首先用有限状态机分析了不重要系数对的嵌入效果,接着利用中心极限定理的原理考察了重要系数对量化后的误差分布,最后,用条件概率的意义,设计了一个简单的统计量作为隐写分析的根据。实验结果表明该统计量适用于中频系数对隐写方法的检测。     

基于DCT变换的图像伪装技术

该文提出一种频域的信息伪装技术,该技术具有以下几个优点:(1)隐藏效果好,人眼系统不能发觉隐藏了秘密图像的载体图像与原载体图像之间的差别;(2)口令控制,只有知晓伪装口令的人才能解密;(3)可以有效地抵抗JEPG等图像压缩编码的破坏;(4)利用载体图像的部分内容可以恢复原秘密图像;(5)该算法可以用于数字水印,而且可以将水印图像由二值图像扩展到灰度图像;(6)算法可以进行多址伪装,即在同一幅载体图像中隐藏多幅秘密图像。     

一种基于图像DCT域信息熵的盲检测算法

提出了一种基于图像DCT域信息熵的盲检测算法。该算法通过分析JPEG图像隐写前后子块DCT系数信息熵的变化,提取JPEG图像子块DCT系数信息熵的64维特征向量,之后用LSSVM分类器对待测图像进行分类,最终达到检测载密图像的目的。实验表明,该算法能有效地针对各种隐写算法下的载密图像进行检测,同时对低嵌入比例下的载密图像也能达到较高的检测率。     

基于辨识性统计特征的PQ隐密图像识别算法

提出一种基于辨识性统计特征的PQ（perturbed quantization）隐密图像识别算法。该算法根据经典PQ隐写对图像数据的更改方式,提取可有效区分该类隐密图像与其他类隐密图像的辨识性统计特征,并运用SVM（support vector machines）分类器进行分类识别。实验结果表明：本算法能够可靠地将PQ隐密图像从5类典型JPEG隐写PQ、F5、nsF5、MB1和MOD的隐密图像中识别出来;即使F5、nsF5、MB1和MOD的隐密图像不参与分类器的训练,本算法仍能有效识别PQ隐密图像。     

SARDH: A novel sharpening-aware reversible data hiding algorithm

Reversible data hiding (RDH) algorithms allow data protection and exact recovery of the original cover image upon data extraction. Most of RDH algorithms attempt to embed data while maintaining high peak signal-to-noise ratio. However, it has been deemed recently that some applications may demand improving the image contrast while embedding data. Additionally, stego images with better contrast could be less attractive to attacker, given the fact they have no idea about the original cover image. In this paper, we propose a sharpening-aware RDH (SARDH) algorithm that is capable of embedding significant amount of data in addition to sharpening the image. Experimental results proved the ability of SARDH algorithm in embedding large payloads and providing sharper stego images.     

CBS: Contourlet-Based Steganalysis Method

An ideal steganographic technique embeds secret information into a carrier cover object with virtually imperceptible modification of the cover object. Steganalysis is a technique to discover the presence of hidden embedded information in a given object. Each steganalysis method is composed of feature extraction and feature classification components. Using features that are more sensitive to information hiding yields higher success in steganalysis. So far, several steganalysis methods have been presented which extract some features from DCT or wavelet coefficients of images. Multi-scale and time-frequency localization of an image is offered by wavelets. However, wavelets are not effective in representing the images in different directions. Contourlet transform addresses this problem by providing two additional properties, directionality and anisotropy. The present paper offers an universal approach to steganalysis called CBS, which uses statistical moments of contourlet coefficients as features for analysis. After feature extraction, a non-linear SVM classifier is applied to classify cover and stego images. The efficiency of the proposed method is demonstrated by experimental investigations. The proposed steganalysis method is compared with two well-known steganalyzers against typical steganography methods. The results showed the superior performance of our method.     

基于DCT系数统计特性的JPEG图像隐写分析

提出了一种基于离散余弦变换（DCT）系数统计特性的JPEG图像隐写分析算法。该算法在分析JPEG图像DCT系数的统计特性的基础上,提取了8维特征向量,通过最小二乘支持向量机（LS—SVM）分类器对待测图像进行分类,以达到检测载密图像的目的。算法实现简单,计算复杂度低。实验结果表明,该算法检测速度快,具有较高的检测正确率,能够实现针对各类JPEG图像信息隐写算法的有效检测。     

多级秘密信息隐藏方法

针对普通的一级秘密信息隐藏的方法具有安全性低,视觉效果差的问题,本文提出了一种多级别信息隐藏的方法.该方法使一级秘密信息在一级密钥作用下成为宿主图像,提高了信息隐藏的安全性,再将宿主图像分成3×3的图像块,在二级密钥的控制下成功将二级秘密信息嵌入.采用图像置乱和LSB算法的结合方法,并在两级秘密信息的作用下,使得载密图...     

Visually meaningful image encryption algorithm based on digital signature

Traditional image encryption algorithms transform a plain image into a noise-like image. To lower the chances for the encrypted image being detected by the attacker during the image transmission, a visually meaningful image encryption scheme is suggested to hide the encrypted image using another carrier image. This paper proposes a visually meaningful encrypted image algorithm that hides a secret image and a digital signature which provides authenticity and confidentiality. The recovered digital signature is used for the purpose of identity authentication while the secret image is encrypted to protect its confidentiality. Least Significant Bit (LSB) method to embed signature on the encrypted image and Lifting Wavelet Transform (LWT) to generate a visually meaningful encrypted image are designed. The proposed algorithm has a keyspace of 139.5-bit, a Normalized Correlation (NC) value of 0.9998 which is closer to 1 and a Peak Signal to Noise Ratio (PSNR) with a value greater than 50 ?dB. Different analyses are also performed on the proposed algorithm using different images. The experimental results show that the proposed scheme is with high key sensitivity and strong robustness against pepper and salt attack and cropping attack. Moreover, the histogram analysis shows that the original carrier image and the final visual image are very similar.     

一种基于JPEG2000的小波域信息隐藏算法

针对JPEG2000基本压缩编码的特点,提出了一种应用于隐蔽通信的基于小波域统计特征的隐写算法.该算法首先利用置乱变换对待隐藏图像进行变换处理,并对载体图像进行多分辨率小波分解,然后根据人类视觉系统的掩蔽特性选择重要小波系数,将隐秘信息分别嵌入到重要小波系数的不同频率域中.实验结果表明,算法提高了信息隐藏的容量,较好地...     

No embedding: A novel image cryptosystem for meaningful encryption

In this paper, we propose a novel image cryptosystem, which enables to encrypt the secret images with a smaller-size cover image. Compared with the existing meaningful encryption methods, our cryptosystem has three advantages: (1) non-embedding encryption, i.e., there isn’t any data embedding into the cover image during the encryption process. (2) Our cryptosystem can simultaneously encrypt multiple secret images with one cover image, which greatly improves the security of secret images. (3) Our cryptosystem can accomplish not only the meaningful encryption, but also the meaningless encryption. Thus, people don’t switch encryption methods when meeting different encryption requirements. Our scheme leverages the popular coupled dictionary learning and compressive sensing techniques to accomplish the whole task. Specifically, we use the coupled dictionaries to build connection between the cover image and the secret image, and apply the compressive sensing to decrypt the secret image. To demonstrate the effectiveness of the proposed cryptosystem, a series of experiments are conducted. Experimental results on gray images and colorful RGB images verify its superiority.