Large-scale Network Anomaly Detecting Method Based on Multi-feature Similarity
Juan Wang · Jisuanji gongcheng · 2007
An anomaly detection model based on the multi-feature similarity in large-scale network is proposed in this paper.The model uses a variety of flux characteristics of the network in large-scale network,after high frequent statistics,the establishment of the character set and the calculation of similarity factors between real-time character sets and standard character sets.The similarities of network flows will be destroyed when large-scale network attacks or viruses.So the network anomaly through comparison with the normal situation can be promptly and accurately found.Experimental results show that the more comprehensive network character detecting model with a single character of detection is lower misstatement,quite applicable to large-scale network.