An adaptive image steganographic scheme based on Noise Visibility Function and an optimal chaotic based encryption method

Steganography is the science of hiding secret message in an appropriate digital multimedia in such a way that the existence of the embedded message should be invisible to anyone apart from the sender or the intended recipient. This paper presents an irreversible scheme for hiding a secret image in the cover image that is able to improve both the visual quality and the security of the stego-image while still providing a large embedding capacity. This is achieved by a hybrid steganography scheme incorporates Noise Visibility Function (NVF) and an optimal chaotic based encryption scheme. In the embedding process, first to reduce the image distortion and to increase the embedding capacity, the payload of each region of the cover image is determined dynamically according to NVF. NVF analyzes the local image properties to identify the complex areas where more secret bits should be embedded. This ensures to maintain a high visual quality of the stego-image as well as a large embedding capacity. Second, the security of the secret image is brought about by an optimal chaotic based encryption scheme to transform the secret image into an encrypted image. Third, the optimal chaotic based encryption scheme is achieved by using a hybrid optimization of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) which is allowing us to find an optimal secret key. The optimal secret key is able to encrypt the secret image so as the rate of changes after embedding process be decreased which results in increasing the quality of the stego-image. In the extracting process, the secret image can be extracted from the stego-image losslessly without referring to the original cover image. The experimental results confirm that the proposed scheme not only has the ability to achieve a good trade-off between the payload and the stego-image quality, but also can resist against the statistics and image processing attacks.     

小波域最小嵌入失真函数设计及其在隐写中的应用

为了提高隐写方案的安全性,提出一种基于最小嵌入失真原理和网格码的图像隐写算法。首先在离散小波域结合人眼视觉特性和整数提升小波变换设计了失真测度函数,主要考虑了亮度、频率和纹理掩蔽因子对载体失真的影响。然后结合网格码设计了隐写算法,将嵌入信息对载体的修改最小化并且集中在人眼不敏感区域。实验结果显示,方案具有良好的视觉不可见性,且能抵抗空域、小波域等隐写分析的攻击,安全容量达到0.4 bits/pixel。     

A novel image steganography scheme with high embedding capacity and tunable visual image quality based on a genetic algorithm

Steganography is knowledge and art of hiding secret data into information which is largely used in information security systems. Various methods have been proposed in the literature which most of them are not capable of both preventing visual degradation and providing a large embedding capacity. In this paper, we propose a tunable visual image quality and data lossless method in spatial domain based on a genetic algorithm (GA). The main idea of the proposed technique is modeling the steganography problem as a search and optimization problem. Experimental results, in comparison with other currently popular steganography techniques, demonstrate that the proposed algorithm not only achieves high embedding capacity but also enhances the PSNR of the stego image.     

基于噪声感知残差网络的JPEG隐写分析方法

为了进一步挖掘自适应JPEG隐写图像中隐写噪声信号特征,提出基于噪声感知残差网络的JPEG隐写分析方法.该方法由噪声感知、噪声分析和判断三部分组成.其中,噪声感知部分提取图像噪声,利用图像去噪网络,更加全面地捕获隐写引入的扰动;噪声分析部分获得噪声信息的统计特征;判断部分确定图像是否携带隐写信息.此外,网络中的残差连接有效融合多尺度特征,并防止训练中出现梯度消失和爆炸.多种条件下的对比实验结果表明,该方法相较于对比算法,能够提升针对JPEG自适应隐写的检测性能并具有更好的泛化能力.     

一种针对LSB匹配隐写的负载定位新算法

针对最不重要比特位(Least significant bit, LSB)匹配隐写算法,本文提出了一种新的负载定位算法。将隐写负载定位看作二分类问题,将载密图像每个像素位置看作待分类样本,通过提取载密图像集中每个像素位置在8个方向上的相邻像素差分平方均值特征,利用支持向量机(Support vector machine,SVM)分类器,将每个像素位置划分到正确的类别——负载位置或非负载位置。本文从理论和实验两方面验证了所提分类特征的有效性。针对LSB匹配隐写,本文方法与最大后验概率(Maximum a posteriori, MAP)载体估计方法做出比较,在低嵌入率条件下,本文方法的定位性能有明显提高。     

Hidden image display which required the special eyeglass for the viewer to observe the hidden image

Stenography is to conceal the hidden information within another information such that the hidden information can be extracted by the special technique. A steganographic display that required the special eyeglass for the viewer to observe the hidden image was newly proposed. In this hidden‐image display, the viewers wearing the special eyeglass can observe the hidden image, while the viewer with the naked eye can not discern the hidden image. Working principle and the calculation scheme for the generation of input images was investigated. The estimation of the normalized luminance for the gray levels of each pixel on the display was required for the calculation. The concept was experimentally verified using the commercial 3D display based on the patterned retarder and the polarizing eyeglass.     

A Novel High Quality High Capacity Image Hiding Scheme Based on Image Compression and an Optical Pixel Adjustment Process

ABSTRACT

Image hiding methods embed a secret image into a host image. The resultant stego-image does not attract the interceptors that would not detect the differences between the host image and the stego-image. To exploit the great developments in the area of image compression and to improve the quality of stego-image, this paper proposes a new method to embed the secret image into the host image. Basically, the secret image is compressed and then embedded into host image. The embedding method is based on the Optimal Pixel Adjustment Process (OPAP) and genetic algorithm. In the paper we addressed the important issues to build such systems. The experimental results showed that the proposed method can improve the quality from 60% to 80% when compared with the simple Least Significant Bit (LSB) replacement methods. Adding to that, the mean square error of the stego-image is much lower compared with other methods (Chan & Cheng, 2004 Chan, C.K. and Cheng, L.M. 2004. Hiding data in images by simple LSB substitution. Pattern Recognition, 37(3): 469–474. [Crossref], [Web of Science ®] , [Google Scholar]; Chang, Hsiao, & Chan, 2003 Chang, C.C., Hsiao, J.Y. and Chan, C.S. 2003. Finding optimal least-significant-bit substitution in image hiding by dynamic programming strategy. Pattern Recognition, 36(7): 1583–1595. [Crossref], [Web of Science ®] , [Google Scholar]; Thien & Lin, 2003 Thien, C.C. and Lin, J.C. 2003. A simple and high-hiding capacity method for hiding digit-by-digit data in images based on modulus function. Pattern Recognition, 36(12): 2875–2881. [Crossref], [Web of Science ®] , [Google Scholar]; Tseng, Chan, Ho, & Chu, 208; Wang, Lin, & Lin, 2001 Wang, R.Z., Lin, C.F. and Lin, J.C. 2001. Image hiding by optimal LSB substitution and genetic algorithm. Pattern Recognition, 34(3): 671–683. [Crossref], [Web of Science ®] , [Google Scholar]). Also, the proposed technique improves capacity. In other words, we can embed a secret image with size 450?×?450 inside a hosting image with size 512?×?512.     

Quadruple Difference Expansion-Based Reversible Data Hiding Method for Digital Images

ABSTRACT

Lossless data hiding is a special type of data hiding technique that guarantees not only the secret data but also the ability of cover media to be reconstructed without any distortion. A latest lossless data hiding technique is proposed by Hong Lin Jin's that is based on hiding only one data bit in the spatial domain in gray-level image. However, this method uses double difference expansion to embed bits which results in a small embedding capacity. For this purpose, we propose an improved algorithm with the potential of increasing the payload capacity and maintaining good image quality. The proposed improved algorithm is characterized by two aspects. First, the proposed improved reversible data hiding scheme is enhanced to exhibit data hiding in color palette images. Second, the embedding level is improved by using quadruple difference expansion to guarantee the embedding of 2-bit data into color images. Experiments of the proposed improved method have been conducted over several well-known test images. The results show that the proposed improved method significantly improves the embedding capacity over Hong Lin Jin's scheme by the range of 15–35% for grayscale images and 20–46% for color images while still maintaining the quality of the stego-images.     

Reference Monitor Technology: Watching Your Every Keystroke

ABSTRACT

In modern electronic communication, ensuring security during transferring of data is crucial. Digital steganography is the technique that ensures the same, in which any secret data is hidden into the cover mediums such as images, audio or video files. Resistance to removal and invisibility of hidden data are the two important requirements of any steganographic system. This paper proposes a new approach to hide any secret data in images. Also, this paper proposes a new approach which hides an executable file in images. The executable files we have considered are Windows PE (Portable-Executable) files. Moreover from the experimental results, it is proven that the proposed approach is suitable for hiding all type of digital files including exe files. Also, comparing with the existing approaches, this approach shows better performance.     

Efficient and secure data hiding in encrypted images: A new approach using chaos

ABSTRACT

The recent trends in technology have made it possible to reproduce and share digital media more easily and more rapidly. This leads to the problem of exploiting the media illegitimately. To alleviate this problem, many cryptographic techniques are used to secure the data by encrypting them. However, the cloaked form of encrypted data attracts the intruder and shows the way to malicious attacks. Due to this, in recent times steganography has drawn more attention to secure the data. This article presents a new technique that embeds data in intermediate significant bit (ISB) and least significant bit (LSB) planes of the cover image. The method employs chaotic maps to generate random locations to hide the data bits as well as permutation order to encrypt the cover image. The cover image is first encrypted by applying permutation order, then embedding is carried out on the random locations generated. After embedding, the decrypted cover image is transmitted. This method provides two-level security in extracting the hidden data. Experimental outcomes (PSNR, MSE, NAE, and NCC) confirm that the method is proficient. The randomness of the values generated by chaotic maps is assessed by the NIST standard test suite.