Network traffic anomalies refer to the traffic changed abnormally and obviously.Local events such as temporary network congestion,Distributed Denial of Service(DDoS)attack and large-scale scan,or global events such as...Network traffic anomalies refer to the traffic changed abnormally and obviously.Local events such as temporary network congestion,Distributed Denial of Service(DDoS)attack and large-scale scan,or global events such as abnormal network routing,can cause network anomalies.Network anomaly detection and analysis are very important to Computer Security Incident Response Teams(CSIRT).But wide-scale traffic anomaly detection requires extracting anomalous modes from large amounts of high-dimensional noise-rich data,and interpreting the modes;so,it is very difficult.This paper proposes a general method based on Principle Component Analysis(PCA)to analyze network anomalies.This method divides the traffic matrix into normal and anomalous subspaces,maps traffic vectors into the normal subspace,gets the distance from detected vector to average normal vector,and detects anomalies based on that distance.展开更多
距离向多孔径SAR模式是一种高分辨率的宽测绘带成像模式。反解运算和成像处理是距离向多孔径成像算法的两个部分,两者合理配合使用是实现多孑L径模式高精度成像的关键。该文给出了一种采用变尺度傅里叶变换(Scaled F T,scF T,)算法来实...距离向多孔径SAR模式是一种高分辨率的宽测绘带成像模式。反解运算和成像处理是距离向多孔径成像算法的两个部分,两者合理配合使用是实现多孑L径模式高精度成像的关键。该文给出了一种采用变尺度傅里叶变换(Scaled F T,scF T,)算法来实现成像处理并与反解运算结合的多孔径成像算法。与已有的处理算法比较,该算法存不显著增加计算钉杂席的条件下可获得较高的成像质量。文巾最后给m了仿真结果。展开更多
基金This work was funded by the High-tech Research and Development Program of China (863 Program) under Grant 2006II01Z451.
文摘Network traffic anomalies refer to the traffic changed abnormally and obviously.Local events such as temporary network congestion,Distributed Denial of Service(DDoS)attack and large-scale scan,or global events such as abnormal network routing,can cause network anomalies.Network anomaly detection and analysis are very important to Computer Security Incident Response Teams(CSIRT).But wide-scale traffic anomaly detection requires extracting anomalous modes from large amounts of high-dimensional noise-rich data,and interpreting the modes;so,it is very difficult.This paper proposes a general method based on Principle Component Analysis(PCA)to analyze network anomalies.This method divides the traffic matrix into normal and anomalous subspaces,maps traffic vectors into the normal subspace,gets the distance from detected vector to average normal vector,and detects anomalies based on that distance.
文摘距离向多孔径SAR模式是一种高分辨率的宽测绘带成像模式。反解运算和成像处理是距离向多孔径成像算法的两个部分,两者合理配合使用是实现多孑L径模式高精度成像的关键。该文给出了一种采用变尺度傅里叶变换(Scaled F T,scF T,)算法来实现成像处理并与反解运算结合的多孔径成像算法。与已有的处理算法比较,该算法存不显著增加计算钉杂席的条件下可获得较高的成像质量。文巾最后给m了仿真结果。
