共查询到18条相似文献,搜索用时 182 毫秒
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在已知嵌入消息长度的条件下,隐写密钥可以看做消息嵌入的起始位。将图像像素划分为不同类点,通过分析信息嵌入和最低位置反对各类点的影响,得到图像嵌入信息部分和未嵌入信息部分的差异,最终设计了针对空域序列LSB(least significant bits)隐写图像的密钥估计算法。实验结果表明,该算法可对隐写密钥进行快速有效的估计。 相似文献
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图像隐写分析就是对信息隐藏系统进行攻击的技术,基于JPEG图像的隐藏信息长度估计的方法最近引起了很大关注。该文分析和讨论了JSteg、F5和OutGuess隐写分析算法。 相似文献
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对空域图像LSB隐写术的提取攻击 总被引:2,自引:0,他引:2
隐写分析的研究一直集中于检测隐藏信息的存在性,而关于如何提取隐藏信息(即对隐写术的提取攻击)的研究还非常少.对于使用密钥的隐写术,提取攻击等价于恢复隐写密钥.文中结合隐写分析中的检测技术和密码分析中的相关攻击技术,对空域图像LSB隐写术提出了一种隐写密钥恢复方法.理论分析说明:此攻击方法的计算复杂度主要由所需的样本量决定,并且当嵌入率r接近0或1时攻击将失败.作者通过混合高斯模型给出了一个估计最小样本量的方法.针对隐写软件"Hide and Seek 4.1"的实验表明:此攻击方法可以成功恢复隐写密钥,从而提取隐藏的消息.如果消息长度L未知,当嵌入率5.3%<r<94.7%时攻击可以成功;如果L已知,当1.1%<r<98.4%时攻击可以成功,并且当11%<r<50%时,使用估计的最小样本量可以将攻击速度提高10%~45%. 相似文献
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图像序列隐写是指利用载体图像特征数据(包括频域数据、空域数据)连续嵌入信息的隐藏方法。本文提出了一种针对图像扩展频谱序列隐写的密钥估计算法。该方法基于序列分析与突变检测的理论,利用序列概率比累积和检验方法(CUSUM-SPRT)对变化进行检测。考虑图像DCT系数满足拉普拉斯分布,给出了理想平稳拉普拉斯分布信号扩展频谱隐藏密钥估计的模型。采用随机微分方程法(SDE)生成拉氏分布的随机序列进行实验。对于非平稳信号的图像数据,在低信噪比(SNR)下,利用当地最有效序列检测法,给出了拉普拉斯分布的密钥估计模型。实验显示,该方法不但能检测出扩展频谱隐写,估计嵌入密钥,而且比Trivedi的方法更有效。 相似文献
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基于图像校准的通用型JPEG隐写分析 总被引:1,自引:0,他引:1
对JPEG图像隐写分析而言,直接在嵌入域中提取特征一般会取得更好的效果.然而,在现有的JPEG隐写术中,由于所嵌入秘密信息的能量要远远小于载体图像本身所具有的能量,因而秘密信息嵌入所引起的载体图像微小失真很难直接从给定的待测图像中发现.基于此,文中在已有JPEG图像全局校准方案的基础上,提出了对JPEG图像进行局部校准的新思路.并在此基础上提出了一种全局与局部校准相结合的通用型JPEG隐写分析算法.通过从待测图像和局部校准图像量化后DCT系数的差分信号中提取特征、以及对从待测图像和全局校准图像分别提取的特征进行差分等方式,使得提取的特征对秘密信息的嵌入更为敏感.此外,文中应用Markov转移概率矩阵,分别提取块内以及横向和纵向块间量化后DCT系数在幅值和符号两个方面的相关性作为特征.仿真结果表明,与已有的JPEG隐写分析算法相比,文中所提出的算法具有更好的检测效果. 相似文献
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针对空域数字水印算法鲁棒性差、难以抵抗较强的攻击的问题,本文提出一种基于支持向量机SVM与结构相似度SSIM的自适应图像数字水印算法。本文利用结构相似度算法SSIM计算不同图像子块的最大水印嵌入强度,通过回归性支持向量机建立不同图像子块与最大水印嵌入强度的相关性模型,实现了根据不同图像子块预测水印嵌入强度。本文在现有基于图像邻域像素之间相关性的时空域数字水印算法的基础上,选取图像中的图像子块进行水印嵌入,通过修改子块中心位置像素值,进行水印嵌入与提取。本文提出的算法在确保水印算法具有较好的透明性的基础上,提高了水印算法的鲁棒性。实验结果表明,该算法在保持较好透明性的基础上,对于JPEG压缩、噪声、中值滤波等攻击具有较强的抵抗能力。 相似文献
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提出了一种基于DCT系数统计特性的JPEG图像定量隐写分析算法。该算法在对JPEG图像DCT系数的统计模型进行研究的基础上,提取了能够反映嵌入容量变化规律的特征参数[α]。以特征参数[α]为基础,提出了基于流形学习的特征提取算法,通过LIB-SVM分类器进行训练,估计隐写对DCT系数的更改比率。实验结果表明,与传统的定量分析算法相比,提出的算法具有更高的估计准确率和稳定性。 相似文献
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At present, steganalysis research focuses on detecting the existence of a hidden message. However, extracting the hidden information, i.e., an extracting attack, is crucial in obtaining effective evidence in computer forensics. Due to the difficulty of an extracting attack, research in this field is limited. In steganography with a stego key, an extracting attack is equivalent to recovering the stego key. In this paper we study a method for recovering the stego key in least significant bit (LSB) steganography with a decompressed JPEG image as the cover image. Firstly, the recovery of the stego key is translated into a cryptanalysis problem for a sequential cipher. The method for recovering the stego key is based on estimating the modification positions. The minimum size of the data used to recover the stego key successfully is discussed. Secondly, when a decompressed JPEG image is used as the cover image, the probability of recovering the cover pixels using recompression is discussed. Recompression is used to compute the error of the estimated sequence. Finally, an algorithm to recover the stego key in LSB steganography with a decompressed JPEG image as the cover image is proposed. The experimental results for the steganographic software, Hide and Seek 4.1 and its variant, which is a typical representative of LSB steganography, show that the proposed method can successfully recover the stego key in LSB replacement and LSB matching, i.e., the extracting attack is successful, and it outperforms three previous methods in terms of computational complexity. 相似文献
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《Intelligent Data Analysis》1999,3(1):75-85
Most of the conventional regression methods can only estimate a piecewise polynomial function in which the exact positions or the probabilistic distribution of the change-points is prespecified. This paper proposes an optimization method to estimate a piecewise polynomial function with unknown change-points. We first express a piecewise function by the addition of some absolute terms. Utilizing the properties of this function, a piecewise regression model is then formulated to minimize the estimation errors subjected to an amount of change-points. The model is then solved by a modified goal programming technique, which is more computationally efficient than conventional goal programs. Numerical examples demonstrate that the proposed method is very promising in estimating the piecewise regression with automatic change-point detection. 相似文献
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针对传统突变点检测算法具有大延时的问题以及实际数据中同时含有突变点、异常点的实际情况,提出一种基于小波变换有效分数向量的异常点、突变点检测算法.该方法通过引入有效分数向量作为检测统计量,有效避免了传统检测统计量随着数据增多而无限增大的缺点;提出利用小波分析统计量的办法,有效地克服了传统突变点检测算法中存在大延时的缺陷;利用李氏指数及小波变换的关系,实现了在一个检测框架内同时在线检测异常点以及突变点,使得该检测算法更符合突变点及异常点同时存在的实际情况.仿真实验和性能比较结果证明了提出的异常点、突变点检测算法具有一定的有效性和实用性. 相似文献
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Change-point detection schemes, which represent one type of anomaly detection schemes, are a promising approach for detecting network anomalies, such as attacks and epidemics by unknown viruses and worms. These events are detected as change-points. However, the schemes generally also detect false-positive change-points caused by other events, such as improper parameter setting of detectors. Therefore there is a requirement for a scheme that detects only true-positive change-points caused by attacks and epidemics by unknown viruses and worms. The true-positive change-points tend to occur simultaneously and intensively in very large numbers, while the false-positive change-points tend to occur independently. Therefore, we expect that the multi-stage change-point detection scheme, which performs change-point detection in a distributed manner and takes account of the correlation among multiple change-points, can exclude false-positive change-points by neglecting those that occur independently. In this paper, we propose the multi-stage change-point detection scheme and introduce a weighting function that gives smaller weight to LDs with higher false-positive rate inferred by GD in order to avoid a set of false-positive alerts generated by the low-accuracy detectors from causing high false-positive rate of the scheme. We evaluate the performance of the scheme by a simulation using the parameter values obtained in an experiment using real random scan worms. In the evaluation, we modify AAWP (Analytical Active Worm Propagation) model so that it can derive the number of infected hosts (i.e., attack hosts) more accurately by considering a failure of infection behavior by random scan worms. The simulation results show that our scheme can achieve an optimal performance (detection rate of 1.0 and false-positive rate of 0) while the stand-alone change-point detection scheme, which does not use the correlation among multiple change-points, cannot attain such optimal performance, and our scheme with alert weighting always shows better detection performance than the scheme without alert weighting. 相似文献
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将基于攻击图的脆弱性评估技术和动态网络演化分析相结合,提出了一种动态攻击网络演化与分析模型。该模型首先借鉴演变图的思想将攻击图拓展为随时间域和空间域同时变化的演变攻击图,在子图相似度定义的基础上构建攻击演化模式,分析模式内暂态变化的同时结合时序数据分析模式间的连接变化,以攻击演变挖掘算法为核心的模型应用分析过程可以确定整个过程中攻击模式的数量,明晰每个模式的典型攻击结构,实例证明本文提出的模型和方法可以有效地模拟攻击发生的过程,当需要防御手段进行干预时,可有针对性的选择危害大的阶段或者节点来抑制攻击过程的发生 相似文献
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基于估计点扩展函数值的湍流退化图像复原 总被引:13,自引:0,他引:13
提出了一种直接从湍流退化图像中估计湍流点扩展函数值的方法.本方法不再利用自然或人工向导星图像来测定点扩展函数,而是直接利用两帧连续短曝光湍流退化图像作为输入,在空域中对其进行适当的延拓,在频域中建立和选择关于湍流点扩展函数离散值的一系列计算方程.为了克服噪声的干扰,在点扩展函数的非负性和空间光滑性的约束条件下,将点扩展函数的计算问题转化为优化估计问题,通过极小化准则函数估计点扩展函数值,进而恢复退化图像.实验结果表明,本文方法十分有效,复原效果好. 相似文献