A Review of Anomaly Detection Techniques in Network Intrusion Detection System
In network security Intrusion detection systems (IDS) are an important element in a network's defenses to help protect against increasingly sophisticated cyber attacks. Intrusions are nothing but attacks. IDS that rely solely on a database of stored known attacks are no longer sufficient for effectively detecting modern day threats. This paper is basically a research paper on network intrusion detection techniques. And also describes what kind of attack took place. This paper presents a novel anomaly detection technique that can be used to detect previously unknown attacks on a network by identifying attack features. In this paper we discussed about various network intrusion detection techniques like K-means clustering, feature selection and decision tree. This paper also includes various examples from the past and current projects. We hope that this survey will provide a better understanding of the different directions in which research has been done on this topic.