针对音频抖动调制QIM隐写的盲检测

分析了抖动调制（DM）QIM隐写生成的携密音频的特征,利用携密音频段间变换域系数差的绝对值绘制直方图,根据该直方图中存在固定间隔跳跃点的特征,提出了一种盲检测算法。实验验证了该检测算法对音频的抖动调制隐写和简单QIM隐写都有效果。     

抗隐写密钥分析的LSB隐写算法

LSB算法是一种典型的空间域信息隐藏算法,由于嵌入信息量大、算法简单而成为最常见的信息隐藏算法,也同时成为了隐写分析者很感兴趣的对象。针对隐写位置密钥的攻击,本文提出了一种改进的LSB隐写算法,先在图像各像素的LSB位嵌入噪声信息,再在密钥的控制下有选择性地在部分像素点嵌入隐藏信息。在已知载体图像或已知多幅用同一载体进行信息隐藏的载密图像的情况下,可以有效抵御针对隐写位置密钥的攻击,提高了LSB算法的安全性。同时该思想也可应用于基于DCT域等频域的隐藏算法中。     

基于手工特征提取与结果融合的CNN音频隐写分析算法

随着互联网技术的快速发展,出现了基于IP的语音传输技术,给人们带来方便的同时也带来了许多安全隐患,如不法分子利用VoIP压缩域语音传输协议传送秘密信息.因此,针对基于G.729A编码的基音隐写算法和互补邻居顶点的量化索引调制音频隐写算法,本文提出了一种基于手工特征提取与结果融合的卷积神经网络音频隐写分析算法.通过将手工提取特征与卷积神经网络相结合,可以实现在VoIP压缩域同时对基于基音的隐写算法和互补邻居顶点的量化索引调制音频隐写算法进行有效检测.实验结果表明,在同时对基音隐写算法和互补邻居顶点的量化索引调制音频隐写算法进行检测时,本文所提出的基于手工特征提取与结果融合的卷积神经网络音频隐写分析算法的检测准确率可以达到86.2％(嵌入率为100％、音频样本时长为0.1s).与现有隐写分析算法相比,在音频时长较短时,本文所提算法取得了优异的检测结果.     

对空域图像LSB隐写术的提取攻击

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%.     

高效±k自适应图像隐写术

自适应隐写可避免修改载体的敏感区域, 有效提高隐写术的安全性. 总结分析了现有自适应隐写的边信息同步方法. 通过推广单调纹理函数思想, 构造一种基于自由度的纹理保序函数, 实现了自适应隐写边信息的快速同步. 结合湿纸编码和多层嵌入思想, 提出自适应 ± 1和± 2 隐写算法. 新算法既保证通信双方能快速同步边信息, 同时具有很高的抗检测性能. 理论分析和实验结果均表明了算法的有效性.     

基于变步长量化的安全图像隐写

图像隐写通过将信息隐藏在载体图像中进行秘密传送,实现隐蔽通信.提出了VSQS图像隐写算法,利用密钥控制生成高斯序列并取整,用于对经伪随机排列后的图像像素进行变步长量化,根据量化像素与秘密信息之间的关系来修改像素,实现信息的嵌入.同时给出了该算法的一种扩展(称为TLQS隐写).实验结果表明,VSQS和TLQS图像隐写可提供较大的隐藏容量,并能抵抗几种常见的隐写分析方法.     

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.     

基于时空相关性的视频隐写分析

视频中的扩频嵌入是一种典型的隐写方法,能够抵抗视频压缩、噪声添加等多种攻击。为了有效检测利用该方法嵌入的隐藏信息,将隐写过程建模为加性高斯噪声的叠加过程,分析了噪声叠加对视频序列的时间相关性和空间相关性的影响,提出了基于时空相关性的隐写分析算法。该算法利用视频序列中各帧的四方向差分直方图度量隐写对空间相关性的影响,同时利用相邻帧帧间差分的直方图度量隐写对时间相关性的影响。与现有算法相比,本文算法实现简单,实验结果表明本文算法具有更好的检测性能。     

基于噪声模型和通道融合的彩色图像隐写分析

彩色图像的隐写分析大多在单信号通道进行,弱化或忽略了彩色图像不同颜色通道的相关性.通过分析彩色图像隐写噪声模型,提出了基于噪声模型和通道融合的通用彩色图像隐写分析算法,算法基于小波滤波,得到待检测图像的噪声小波系数子带,从该类子带中提取刻画噪声通道融合特征的噪声梯度方向序列及噪声梯度和序列,结合描述彩色图像颜色通道融合特征的颜色梯度方向序列及颜色梯度和序列,应用HHT变换提取各序列的振荡特征,构建基于Hilbert谱的特征向量,应用SVM分类器进行分类判别.实验表明,与已有的彩色图像隐写分析算法比较,所提出的算法误检率低,具有更好的检测效果.     

针对LSB匹配隐写的图像复原隐写分析

最低有效位(LSB)匹配隐写是目前图像隐写分析的难点和热点之一.为了提高针对LSB匹配隐写的隐写分析算法性能,将图像退化复原理论与图像隐写分析相结合,提出一种新的隐写分析算法.首先将LSB匹配隐写过程建模为加性噪声造成的图像退化过程,提出了一种专用复原滤波算法;然后将载密图像的复原图像作为载体图像的估计图像,提取载密图像与估计图像的质心特征,结合Fisher线性判决器实现隐写分析.实验结果表明,复原滤波算法可有效地复原受LSB匹配隐写噪声污染的退化图像,隐写分析算法的总体性能优于Ker方法,尤其在低嵌入率条件下表现良好,适用于空间域图像LSB匹配隐写.     

Asymptotical synchronization for delayed stochastic neural networks with uncertainty via adaptive control

In this paper, the problem of the adaptive synchronization control is considered for neural networks with uncertainty and stochastic noise. Via utilizing stochastic analysis method and linear matrix inequality (LMI) approach, several sufficient conditions to ensure the adaptive synchronization for neural networks are derived. By the adaptive feedback methods, some suitable parameters update laws are found. Finally, a simulation result is provided to substantiate the effectiveness of the proposed approach.     

变时滞随机忆阻器神经网络的同步控制

在实现实际的复杂人工神经网络模型以及大规模集成电路时,随机噪声是不可避免的.因此,随机忆阻器神经网络具有重要的现实研究意义.针对变时滞随机忆阻器神经网络的同步控制问题,基于非光滑分析以及集值映射、随机微分包含的理论,利用Lyapunov函数和基本不等式的方法,设计了一个线性反馈控制器.通过恰当选择控制器增益,实现了随机忆阻器神经网络驱动系统与相应的响应系统之间的指数同步,所得到的结果保守性更小.最后,给出数值例子验证了理论结果的有效性.     

Analysis of noise-induced phase synchronization in nervous systems: from algorithmic perspective

In many cases, a key step in neuronal information processing is phase synchronization of neurons (as oscillators). Substantial evidence suggests that an universal mechanism is behind the synchronization. Recently, stochastic equations were proposed to model the synchronization. However, it is unclear what force ultimately drives this universal mechanism. From algorithmic perspective, we analyze solutions of these stochastic equations. The result enhances the current analysis for the phase synchronization; importantly, it shows that noise is the ultimate driving force.     

Global Synchronization for Discrete-Time Stochastic Complex Networks With Randomly Occurred Nonlinearities and Mixed Time Delays

In this paper, the problem of stochastic synchronization analysis is investigated for a new array of coupled discrete-time stochastic complex networks with randomly occurred nonlinearities (RONs) and time delays. The discrete-time complex networks under consideration are subject to: 1) stochastic nonlinearities that occur according to the Bernoulli distributed white noise sequences; 2) stochastic disturbances that enter the coupling term, the delayed coupling term as well as the overall network; and 3) time delays that include both the discrete and distributed ones. Note that the newly introduced RONs and the multiple stochastic disturbances can better reflect the dynamical behaviors of coupled complex networks whose information transmission process is affected by a noisy environment (e.g., internet-based control systems). By constructing a novel Lyapunov-like matrix functional, the idea of delay fractioning is applied to deal with the addressed synchronization analysis problem. By employing a combination of the linear matrix inequality (LMI) techniques, the free-weighting matrix method and stochastic analysis theories, several delay-dependent sufficient conditions are obtained which ensure the asymptotic synchronization in the mean square sense for the discrete-time stochastic complex networks with time delays. The criteria derived are characterized in terms of LMIs whose solution can be solved by utilizing the standard numerical software. A simulation example is presented to show the effectiveness and applicability of the proposed results.      

随机干扰下拓扑时变Kuramoto网络事件触发固定时间同步

本文针对一类网络拓扑时变且耦合通道存在随机干扰的Kuramoto型振子网络的同步问题, 设计了事件触 发机制下的固定时间控制算法. 针对耦合网络的拓扑在切换中保持连通的假设, 给出了一种具有多层结构的事件 触发分布式控制策略, 并能够抵消随机干扰对同步性能带来的负面影响. 利用随机Lyapunov稳定理论和固定时间稳 定性理论给出了达到实际固定时间相位同步的控制参数条件和同步调节时间的上界. 另外, 证明了所使用的事件 触发机制在引入双曲正切函数之后不会产生Zeno现象, 并给出了触发间隔的下界. 同时, 在推论中给出了本文提出 的控制方法也可以应对振子耦合拓扑图不连通情况的结论. 最后, 通过两组具有不同噪声强度的仿真实验验证了理 论分析结果.     

调频随机共振实现大参数信号检测

针对传统随机共振只适用于检测低频信号的约束,提出用被测信号和背景噪声调制频率的方法,实现在大参数情况下从强噪声中检测微弱信号.分析了调频信号的频谱,理论分析和数值仿真表明:此方法能降低噪声的有效强度,调频信号中含有的低频分量能产生明显的随机共振.     

Research on the new dynamics properties for a noise-induced excited system

Three induces are discussed to study the new dynamics properties both analytically and numerically for noise-induced Fitzhugh-Nagumo system; the three induces are as follows: Lyapunov exponent, the density distribution of trajectories and power spectrum; the numerical experiment indicated that the noise can induce the system to quite regular dynamics, including coherence resonance (in the case of uncoupling) and stochastic synchronization (in the case of coupling), noise can control the dynamics properties and some other new phenomena that the synchronization takes place only for some moderate noise intensity is also found for the first time.     

Chaotic laser synchronization and its application in optical fiber secure communication

In this paper, optical fiber chaotic secure communication is proposed bycoupling chaotic laser synchronous system with optical fiber propagation channel.Feedback synchronous system of chaotic semiconductor lasers is presented andsynchronous error and decoding formulae are demonstrated. Synchronization betweentwo chaotic laser systems with distributed feedback semiconductor lasers at wavelengthof 1.31 μm is simulatively achieved with almost zero synchronous error. Parametermismatch, synchronous transient response and noise effect on the system are studied.Robustness of synchronization and anti-perturbation can increase by increasing thefeedback coefficient of the system. Influence of group-velocity-dispersion and self-phasemodulation of optical fiber on chaotic laser signal and synchronization are analyzed, and itis found that group-velocity-dispersion affects pulse shape, synchronization and decoding,and limits optical fiber propagation distances, and self-phase modulation does not affectpulse shape, w     

Adaptive observer-based synchronization of the nonlinear nonpassifiable systems

The general approach to synchronization of the dynamic systems on the bassis on the adaptive observer and the passification method was extended to the nonpassifiable nonlinear systems—in particular, to those whose model has the relative order higher than one. Two schemes of synchronization relying on the extended-error adaptive observers and the high-order tuning algorithms were proposed. Solution of the problem of synchronization relies on a new canonical form of the adaptive observer. The conditions for convergence of the parameter estimates to the true values in the case of no system noise were established, and also robustness of the adaptive synchronization to the bounded measurement error was proved. The feasibility of information transmission by modulation of the chaotic signal with the use of the proposed method was demonstrated by the example of the controllable Lorentz system.     

Adaptive chaos synchronization in Chua's systems with noisy parameters

Using the Lyapunov stability theory an adaptive control is proposed for chaos synchronization between two Chua systems which have stochastically time varying unknown coefficients. The stochastic variations of the coefficients around their unknown mean values are modeled through Gaussian white noise produced by the Wiener process. It is shown that using the proposed adaptive control the mean square of synchronization error converges to an arbitrarily small bound around zero depending on the controller feedback gain. Simulation results indicate that the proposed adaptive controller has a high performance in synchronization of chaotic Chua circuits in noisy environment.