A network anomaly detection method based on genetic algorithm
Qinggang Su, Jingao Liu · 2017
With the rapid development of computer network application, it is increasingly important to detect abnormal behaviors and patterns in the field of network security. In this paper, a genetic algorithm is proposed to detect the network anomaly by using Management Information Base (MIB), which is based on the theory of classification using integrated IF-THEN rules. This paper presents a new chromosome coding scheme, and a new method of sufficiency function design is discussed too. Some experiments based on a big data set from real network environment were designed and tested, the results show that this algorithm is efficient in network anomaly detection.