A study on IDS for preventing Denial of Service attack using outliers techniques

Denial of service attack permits the intruders to access the network services thereby preventing the legitimate users to access the services. To overcome the deficits of the DoS attack, it is very essential to design an intrusion detection system. Intrusion detection system (IDS) is software that operates as a network security mechanism to protect the computer network system from attacks. With increasing number of data being transmitted gradually from one network to another, the IDS identify the intrusions in such large datasets effectively. Data mining is an efficient tool applied to outline the intrusion detection system and prevent the massive network data from the intruders. Outliers are patterns in data that do not match to a well-defined notion of normal behavior. Outlier detection aims to find patterns in data that do not conform to expected behavior. It is widely used for developing intrusion detection in cyber security. This paper presents the study of outlier detection technique and how it is used to develop the intrusion detection system to overcome the DOS attack.