Anomaly Detection in Network Using Data Mining Techniques
As the network dramatically extended security considered as major issue in networks. There are many methods to increase the network security at the moment such as encryption, VPN, firewall, etc. but all of these are too static to give an effective protection against attack and counter attack. The authors use data mining algorithm and apply it to the anomaly detection problem. In this paper, their aim to use data mining techniques including classification tree and support vector machines for anomaly detection. The result of experiments shows that the algorithm C4.5 has greater capability than SVM in detecting network anomaly and false alarm rate by using 1999 KDD cup data.