A robust and secure key-frames based video watermarking system using chaotic encryption

Multimedia Tools and Applications - Currently we are facing a wide interest in multimedia security and copyright protection due to the explosion of data exchange in the Internet and the extensive...     

A statistical model for undecidable viral detection

This paper presents a statistical model of the malware detection problem. Where Chess and White (An undetectable computer virus. In: Virus Bulletin Conference, 2000) just partially addressed this issue and gave only existence results, we give here constructive results of undetectable malware. We show that any existing detection techniques can be modelled by one or more statistical tests. Consequently, the concepts of false positive and non detection are precisely defined. The concept of test simulability is then presented and enables us to gives constructive results how undetectable malware could be developped by an attacker. Practical applications of this statistical model are proposed. Finally, we give a statistical variant of Cohen’s undecidability results of virus detection.     

一种基于双流网络的Deepfakes检测技术

随着深度学习技术的飞速发展,以Deepfakes为代表的深度伪造技术开始充斥在互联网上的各个角落。Deepfakes借助于生成对抗网络和自动编码器技术,能够轻松替换人脸以及篡改人的表情信息。此类Deepfakes假视频可以制作虚假色情影片、谣言,传播假新闻,甚至影响政治选举,带来的社会影响极其恶劣。然而,针对此类伪造视频的检测技术还远远落后于生成技术,已有的工作都存在一定的局限性,并不能较好地对Deepfakes视频进行检测。本文首先对现有生成和检测工作进行综述,并分析了现有工作的缺陷,然后提出了基于EfficientNet的双流网络检测框架。通过在大规模开源数据集FaceForensics++测试,我们的检测技术可以在检测Deepfakes类假视频上平均准确率达到99%以上,并一定程度提高模型对抗压缩的能力。     

改进的基于统计模型的前景检测方法

针对基于统计模型的前景检测方法进行改进:一方面,背景模型中记录特征向量属于背景的历史最大概率,在当前帧像素点特征向量与背景模型中已有特征向量匹配时,利用历史最大概率提高其更新速度,使其尽快融入背景;另一方面,对利用贝叶斯决策规则检测的前景目标,剔除其轮廓信息后与背景的空间特征进行匹配,减少阴影对前景检测的影响。实验结果表明,与MoG方法和Li的统计模型方法的前景检测相比,该方法在阴影剔除以及大目标物体遮挡背景恢复等方面都有明显改进。     

A statistical technique for comparing the accuracies of several classifiers

The problem of comparing the accuracies of several classifiers that have been applied to the same set of observations is considered. A strategy based on the application of repeated measures analysis procedures to dichotomous data is proposed for making the comparison. The strategy is illustrated using a set of data taken from the literature.     

基于统计特征的鲁棒图像拷贝检测技术

抗几何攻击的拷贝检测技术是图像拷贝检测领域中的一个重要问题,现有的图像拷贝检测方法中,多数对类似噪声的图像失真比较鲁棒,而对于几何类失真则比较脆弱.因此,提出一种鲁棒图像拷贝检测技术,利用图像高斯过滤后的低频部分中的统计特征(直方图形状和均值)进行拷贝检测.实验结果表明该方法能较好地抵抗不改变内容的几何失真和图像处理攻击.     

A statistical approach to predictive detection

Service providers typically define quality of service problems using threshold tests, such as “Are HTTP operations greater than 12 per second on server XYZ?” Herein, we estimate the probability of threshold violations for specific times in the future. We model the threshold metric (e.g., HTTP operations per second) at two levels: (1) non-stationary behavior (as is done in workload forecasting for capacity planning) and (2) stationary, time-serial dependencies. Our approach is assessed using simulation experiments and measurements of a production Web server. For both assessments, the probabilities of threshold violations produced by our approach lie well within two standard deviations of the measured fraction of threshold violations.     

基于统计特征的JPEG图像通用隐写分析

分析了嵌入信息前后原始图像与隐密图像之间统计特征的差异,根据隐密图像,采用裁剪、重压缩的方法,得到图像F2来代替原始图像,利用15个向量函数提取出特征进行实验,并运用支持向量机(SVM)对待测图像分类,得到了较好的效果.     

A copy-move image forgery detection technique based on Gaussian-Hermite moments

Multimedia Tools and Applications - Images are one of the most prominently used digital information sharing medium now a days. Due to availability of state-of-the-art image editing tools it has...     

基于模糊熵聚类的运动变化区域检测技术

首先讨论了基于帧差分的视频对象分割一般理论模型。在此基础上，利用模糊熵聚类方法提出了一种视频运动变化区域自动检测的算法：通过模糊分类准则在差分图像中对运动变化区域和相对噪声区域进行划分，从而得到运动变化区域。文中仿真实验结果表明．将模糊熵算法运用到差分图像中检测运动变化区域的方法是切实可行的。     

Identification of piecewise affine systems based on statistical clustering technique

This paper is concerned with the identification of a class of piecewise affine systems called a piecewise affine autoregressive exogenous (PWARX) model. The PWARX model is composed of ARX sub-models each of which corresponds to a polyhedral region of the regression space. Under the temporary assumption that the number of sub-models is known a priori, the input-output data are collected into several clusters by using a statistical clustering algorithm. We utilize support vector classifiers to estimate the boundary hyperplane between two adjacent regions in the regression space. In each cluster, the parameter vector of the sub-model is obtained by the least squares method. It turns out that the present statistical clustering approach enables us to estimate the number of sub-models based on the information criteria such as CAIC and MDL. The estimate of the number of sub-models is performed by applying the identification procedure several times to the same data set, after having fixed the number of sub-models to different values. Finally, we verify the applicability of the present identification method through a numerical example of a Hammerstein model.     

基于时域统计变化检测实时分割头肩视频序列

分析了头肩视频序列的特点,提出了基于时域统计变化检测、利用多帧运动信息实时分割视频对象的方法。先选取包括当前帧在内的前连续2N帧图像,将奇数帧与偶数帧图像作差值,形成长度为Ⅳ的帧差图像序列;对每个象素点时域上的Ⅳ个帧差样本值进行分布显著性检验,判断象素点是否发生了变化;对得到的二值图像进行形态学处理,得到完整的分割结果。试验结果表明,该算法能够自动实时的分割视频对象。     

基于统计学特征的android恶意应用检测方法

Android系统作为世界上最流行的智能手机系统,其用户正面临着来自恶意应用的诸多威胁。如何有效地检测Android恶意应用是非常严峻的问题。本文提出基于统计学特征的Android恶意应用检测方法。该方法收集5560个恶意应用和3000个良性应用的统计学特征作为训练数据集并采用聚类算法预处理恶意数据集以降低个体差异性对实验结果的影响。另一方面,该方法结合特征和多种机器学习算法（如线性回归、神经网络等）建立了检测模型。实验结果表明,该方法提供的两个模型在时间效率和检测精度上都明显优于对比模型。     

基于统计质量控制的测距故障检测方法

卫星导航接收机在城区环境使用时,多径信号的存在使得码自相关函数发生畸变,从而导致测距结果与真实距离间出现较大偏差。现有的接收机基带多径消除算法复杂度高,实现较为困难。而接收机自主正直性监测(RAIM)算法的故障检测能力有限,难以同时检测多个测距故障。提出使用统计质量控制方法来实现对测距故障的检测,根据质量控制图的输出结果调整测距信息在定位解算中的权重,从而提高定位精度。该方法能够对每颗卫星的码跟踪性能进行单独监测,算法实现的复杂度低。仿真结果表明:使用该方法能够有效指示多径信号导致的测距误差,从而为改善城区环境下的定位精度提供了新思路。     

Fast parametric curves detection based on statistical hypotheses estimation

We propose a new fast and reliable algorithm of parametric curves detection on images. In our approach as well as in many other approaches based on the Hough transform, we analyze the set of points obtained by an edge detector. Edge points are collected into chains of connected pixels, and then they are analyzed as a whole and piecemeal. At first we use randomized methods to reject unsuitable models. It gives us a high performance. Model parameters of fragments remained after randomized methods are estimated by the least squares method and the reliability of the hypothesis is estimated by the chi-square criterion. Then if the chi square criterion shows higher reliability for the merged similar models, we merge the obtained models.     

A neighborhood-characteristic-based detection model for statistical fragile watermarking with localization

Statistical fragile watermarking is capable of accurately locating tampered pixels and resisting the collage attack. However, the constraint of the tamper ratio may be too stringent. This paper proposes a neighborhood characteristic based detection model for statistical fragile watermarking to lift the constraints of the tampered area from 4% to 14% of the host image. The neighborhood characteristic is used to effectively decrease the probability of false rejection, while the low probability of false acceptance is guaranteed by selecting proper threshold. The tamper detection performance of the proposed detection model is analytical analyzed in the different conditions. Analytical and experimental results demonstrate that the neighborhood characteristic based detection model effectively reduce the total number of false decisions and detect the tampered pixels with high probability.     

基于图像处理的人造板孔穴含量统计的新方法

针对人造板横切面孔穴含量的微观图像的特点,经常要对一幅图像中多个连通区域的面积进行计算。因此,提出了一种通过一次扫描图像,即能快速求出图像中多个连通区域的面积的新方法,并通过实验对两种封闭区域面积统计方法进行比较。结果表明在处理连通区域较多的面积统计时,新方法计算速度较快。     

A non-invasive cancer gene detection technique using FLANN based adaptive filter

Microsystem Technologies - In recent years advancement in cross field technologies lead the world to the new era of genomic research. Several new technologies have been developed for early...     

Corner based statistical modelling in vehicle detection under various condition for traffic surveillance

The paper proposes a robust approach to detect and track the vehicle under various climatic conditions and in the presence of camera shake, shadows, sudden illumination change. Corners have significant features to detect and track the vehicle. Corner points from the vehicular region are segmented from non - vehicular regions based on the statistical background corner point model. The foreground corner points that belong to the vehicular region are grouped using Euclidean distance as they are closely associated with each other. The flickering effects caused by the corner detection algorithm are handled by tracking these corner points. The detection accuracy of the algorithm is 94.32%.