Analyzing Denial-of-service Attacks in KDD CUP 99 Data Set for Intrusion Detection System

Abstract

Recently cyber security has emerged as an established discipline for computer systems and infrastructures with a focus on protection of valuable information stored on those systems from adversaries who want to obtain, corrupt, damage, destroy or prohibit access to it. One of the securitythreat which is difficult to address using traditional network security techniques is Denial of Service (DoS) attacks. We have seen increasing numbers of denial of service (DoS) attacks against online services and web applications either for extortion reasons, or for impairing and even disabling the competition. This paper implemented that how much these (DoS) attacks stand on a top role above on the other attacks. We evaluate those results on four attack categories as found in the KDD Cup 99 intrusion detection datasets, which is widely used as one of the publicly available data sets for network-based anomaly detection system such as Intrusion Detection System (IDS).