CAJ | 학술논문

基于模糊相对熵的网络异常流量检测方法可以在缺乏历史流量数据的情况下，通过对网络流量特征进行假设检验，实现对网络异常行为的检测发现。通过搭建模拟实验环境，设计测试用例对基于模糊相对熵的网络异常流量检测方法进行多测度测试验证，结果表明该方法在设定合理模糊相对熵阈值的情况下检测率可达84.36%，具有良好的检测效率。
기우모호상대적적망락이상류량검측방법가이재결핍역사류량수거적정황하，통과대망락류량특정진행가설검험，실현대망락이상행위적검측발현。통과탑건모의실험배경，설계측시용례대기우모호상대적적망락이상류량검측방법진행다측도측시험증，결과표명해방법재설정합리모호상대적역치적정황하검측솔가체84.36%，구유량호적검측효솔。
In the absence of historical traf ic data,through the network traf ic characteristics of hypothesis test ,Network anomaly traf ic detection method based on r fuzzy elative entropy can detect the network abnormal behavior.This paper constructs the model experimental environment, designs test-cases to multi-measure and verify the network anomaly traf ic detection method based on fuzzy relative entropy.The results show that detection rate of the method can reach 84.36%in the case of set ing reasonable fuzzy relative entropy threshold,the method has the good detection ef iciency.