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针对空间域LSB匹配隐写,提出了一种基于像素差分相关性的隐写分析方法.采用图像的直方图、差分直方图的平滑度、梯度能量、图像平滑度,像素差分的一维和高维统计分布等作为分类特征,结合Fisher线性判别进行隐写分析.实验结果表明,新算法对于LSB匹配的检测具有较高的准确性,且计算复杂度低.该算法还可应用于其他空间域隐写方法的检测. 相似文献
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Steganalysis of stochastic modulation steganography 总被引:1,自引:0,他引:1
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- … 相似文献
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基于图像平滑度的空域LSB嵌入的检测算法 总被引:1,自引:0,他引:1
对图像像素值与邻域均值的差的分布进行建模,以该分布的方差定义了图像平滑度的概念,进而通过对消息嵌入、LSB平面取反带来的图像平滑度的变化进行分析,提出了针对空域LSB替换伪装算法的秘密消息长度估计算法,该算法可以准确地估计图像中嵌入的秘密信息数据量的大小.文中算法物理意义直观、实现简单、计算量小、计算速度快,有利于实现实时检测.实验结果表明该方法是有效的. 相似文献
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为进一步增强图像隐写分析的实用性,对内容自适应隐写术和非内容自适应LSB matching的隐写像素定位问题展开研究,提出一种端到端的图像隐写定位网络PSL_NET,在输入端输入一张图像,输出端定位出图像的隐写像素的位置。在预处理层中,利用空域富模型的高通滤波器提取残噪图像;在深度残差层中,通过深度残差学习增强隐写特征的表达能力;在像素预测层中,利用标记出隐写像素实际位置的掩码图像进行有监督地学习,增强网络对局部隐写像素的感知能力,无区别对待平滑或者纹理区域的像素,逐一预测图像每位像素是真实位或是隐写位,最终预测出图像的隐写像素位;从目标函数层面解决正负样本的不均衡问题,提升检测精度。在基于BOSSbase v1.01数据源展开的实验中,该网络对经自适应隐写术S-UNIWARD在负载为0.4?BPP嵌入的隐写图像的像素检测准确度为0.981?74,实验验证该网络同时适用于对经非内容自适应隐写术LSB matching嵌入后的隐写图像进行隐写像素定位。 相似文献
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Steganalysis always concentrates on the detection of the existence of the hidden information embedded into some digital multimedia by steganography. This paper presents a novel steganographic payload location method for spatial least significant bit (LSB) steganography with the JPEG-decompressed images used as the cover images. Firstly, we discuss the possibility of recovering the original cover image and compute the probability of successfully recovering. Then, we compute the distributions of the difference values between the estimated cover pixels and stego pixels in the payload-carrying and no-payload-carrying positions. Finally, combining with the theory of hypothesis test, we present a method to locate the payload-carrying pixels of JPEG-decompressed images, which is suitable for both LSB replacement and LSB matching. The experimental results show that: 1) the number of stego images needed to accurately locate all the payload-carrying pixels in the proposed method approaches the lower bound; 2) given the number of stego images, in the proposed method, the number of the payload-carrying pixels precisely located approaches the upper bound; 3) the proposed method performs better than some current state-of-the-art steganographic payload location methods for JPEG-decompressed images. 相似文献
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基于Markov链安全性的LSB匹配隐写算法 总被引:1,自引:0,他引:1
隐秘信息的安全性是隐写算法关注的核心问题之一,设计大容量、高安全性的隐写嵌入算法是隐写方法的研究重点.基于Markov链安全标准,以Markov链散度距离最小作为优化嵌入条件,指导LSB匹配嵌入函数,提出了一种优化LSB匹配隐写算法.实验表明该隐写算法在大容量嵌入的同时,保持了载密图像的二阶统计特性,提高了隐写的安全性. 相似文献
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F5 steganography is much different from most of LSB replacement or matching steganographic schemes, because matrix encoding is employed to increase embedding efficiency while reducing the number of necessary changes. By using this scheme, the hidden message inserted into carrier media imperceptibly can be transferred via a more secure subliminal channel. The embedding domain is the quantized DCT coefficients of JPEG image, which makes the scheme be immune to visual attack and statistical attack from the steganalyst. Based on this effective scheme, an extended matrix encoding algorithm is proposed to improve the performance further in this paper. By changing the hash function in matrix encoding and converting the coding mode, the embedding efficiency and embedding rate get increased to a large extent. Eventually, the experimental results demonstrate the extended algorithm is superior to the classic F5 steganography. 相似文献
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In this paper, a novel steganographic method is proposed employing an immune programming strategy to find a near-optimal solution for the pair-wise least-significant-bit (LSB) matching scheme. The LSB matching method proposed by Mielikaien utilizes a binary function to reduce the number of changed pixel values. However, his method still has room for improvement. A tier-score system is proposed in this paper to assess the performance of different orders for LSB matching. An immune programming approach is adopted to search for a near-optimal solution among all the permutation orders. The proposed method can reduce the distortion of the stego image, improve the visual quality, and decrease the probability of detection. The experimental results show that the proposed method achieves better performance than Mielikainen’s pair-wise LSB matching method in terms of distortion and survival probability against steganalysis. 相似文献
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基于Arnold变换与改进LSB嵌入方案的信息伪装算法 总被引:4,自引:0,他引:4
文章提出了一种基于二维Arnold变换与改进LSB嵌入方案的图像信息伪装算法,在对图像进行二维Arnold变换的基础上,采用改进的LSB嵌入方案嵌入数据,提取时只需提取Arnold变换图像的LSB即可。该算法结合了图像置乱技术和改进的LSB嵌入方案,对嵌入的数据形成了双层保护。实验结果表明,该算法的数据嵌入量及失真度与传统的LSB嵌入方式一致,同时能够有效地抵抗RS(RegularSingular)和SPA(SamplePairAnalysis)隐写分析,并保持了图像的直方图统计特征,此外,该方法适用于灰度图像和彩色图像,易于实现。 相似文献
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该文介绍了一种基于图像相近颜色对的RQP信息隐藏检测算法,并提出了可靠估计隐藏信息长度的方法。信息的LSB嵌入会引起图像颜色对的变化,通过对这一变化过程建模可以可靠地估计隐藏信息的长度。该方法简单实用,实验结果表明,对彩色BM P图像具有较高的准确率。该方法同样适用于其它类型图像的LSB信息隐藏。 相似文献
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Image complexity and feature mining for steganalysis of least significant bit matching steganography
The information-hiding ratio is a well-known metric for evaluating steganalysis performance. In this paper, we introduce a new metric of image complexity to enhance the evaluation of steganalysis performance. In addition, we also present a scheme of steganalysis of least significant bit (LSB) matching steganography, based on feature mining and pattern recognition techniques. Compared to other well-known methods of steganalysis of LSB matching steganography, our method performs the best. Results also indicate that the significance of features and the detection performance depend not only on the information-hiding ratio, but also on the image complexity. 相似文献
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Vajiheh Sabeti Shadrokh Samavi Shahram Shirani 《Multimedia Tools and Applications》2013,64(3):777-793
Adaptive steganography methods tend to increase the security against attacks. Most of adaptive methods use LSB flipping (LSB-F) for embedding part of their algorithms. LSB-F is very much vulnerable against simple steganalysis methods but it allows the adaptive algorithms to be extractable at the receiver side. Use of LSB matching (LSB-M) could increase the security but extraction of data at the receiver is difficult or, in occasions, impossible. There are numerous attacks against LSB-M. In this paper we are proposing an adaptive algorithm which, unlike most adaptive methods, uses LSB-M as its embedding method. The proposed method uses a complexity measure based on a local neighborhood analysis for determination of secure locations of an image. Comparable adaptive methods that use LSB-M suffer from possible changes in the complexity of pixels when embedding is performed. The proposed algorithm is such that when a pixel is categorized as complex at the transmitter and is embedded the receiver will identify it as complex too, and data is correctly retrieved. Better performance of the algorithm is shown by obtaining higher PSNR values for the embedded images with respect to comparable adaptive algorithms. The security of the algorithm against numerous attacks is shown to be higher than LSB-M. Also, it is compared with a recent adaptive method and is proved to be advantageous for most embedding rates. 相似文献
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为解决各类数字图像的隐写容量无法统一衡量的问题,提出了数字图像的最大隐写容量归一化的算法.在阐述最低有效位(LSB)隐写技术的基础上,表明了至多改变一位后的图像的最大嵌入容量小于等于像素数的2倍,实现数字图像的最大隐写容量的归一化,将批量隐写最大容量增加了1倍.在阐述和归纳图像隐写规则后,提出了相应的隐秘信息嵌入和提取算法,并通过实例验证了所提算法的有效性,为数字图像的隐写容量归一化提供了可行的解决途径. 相似文献