Data Mining Vs Statistical Techniques for Classification of NSL-KDD Intrusion Data
Intrusion is a kind of malicious attack and is very harmful for individual or for any organization. Due to rapid growing of internet users it has become an important research area Information and network security is becoming an important issue for any organization or individual to protect data and information in their computer network against attacks. In this paper, two categories of techniques: statistical techniques and data mining technique, one methods from each technique is considered for comparative study, these are decision tree technique C5.0 and Support Vector Machine (SVM) applied on widely used intrusion data i.e. NSL-KDD data set downloaded from UCI repository site.