A NOVEL METHOD FOR NETWORK WORM DETECTION BASED ON WAVELET PACKET ANALYSIS

Objective To detect unknown network worm at its early propagation stage. Methods On the basis of characteristics of network worm attack, the concept of failed connection flow （FCT） was defined. Based on wavelet packet analysis of FCT time series, this method computed the energy associated with each wavelet packet of FCT time series, transformed the FCT time series into a series of energy distribution vector on frequency domain, then a trained K-nearest neighbor （KNN） classifier was applied to identify the worm. Results The experiment showed that the method could identify network worm when the worm started to scan. Compared to theoretic value, the identification error ratio was 5.69%. Conclusion The method can detect unknown network worm at its early propagation stage effectively.     

THE INFLUENCE OF SELECTING RECEIVING SLITS AND USING RANDOMLY ORIENTED STANDARD SAMPLES ON QUANTITATIVE TEXTURE ANALYSIS

The influence of the selection of receiving slits and the use of standard samples with random orientation on the result of quantitative texture analysis was tested and discussed. The result proves that it will improve the precision of the analysis to use proper slits and a randomly oriented standard sample. A simple method was given to interpolate the correction curves of random intensities.     

基于小波变换的纹理边缘检测方法

根据Ｍａｌａｔ多尺度边缘检测原理和纹理图像的局部特征,推广了Ｍａｌａｔ多尺度边缘检测算法．这个推广算法不仅适用于一般图像的边缘检测,而且还可用来提取纹理图像的边缘．     

ACCELERATED SUBSPACE ITERATION METHOD FOR GEN-ERALIZED EIGENPROBLEMS USING DYNAMIC CONDENSA-TION TECHNIQUE

Ｎ－ＥＲＡＬＩＺＥＤ ＥＩＧＥＮＰＲＯＢＬＥＭＳ ＵＳＩＮＧ ＤＹＮＡＭＩＣ ＣＯＮＤＥＮＳＡ－ＴＩＯＮ ＴＥＣＨＮＩＱＵＥTX＠瞿祖清＠华宏星＠傅志方ＩｎｔｒｏｄｕｃｔｉｏｎＴｈｅｐｒｏｂｌｅｍｏｆｄｅｔｅｒｍｉｎｉｎｇａｓｕｆｉｃｉｅｎｔｎｕｍｂｅｒｏｆ...