A Survey of Anomaly Detection Methods in Networks

Despite the advances reached along the last 20 years, anomaly detection in networks is still an immature technology, Nevertheless, the benefits which could be obtained from a better understanding of the problem itself as well as the improvement of these methods. Therefore, in this paper we present a survey on anomaly detection in networks. In order to distinguish between the different approaches used for anomaly detection in networks in a structured way, we have classified those methods into four categories: statistical anomaly detection, classifier based anomaly detection, anomaly detection using machine learning and finite state machine anomaly detection. We describe each method in details and give examples for its applications in networks.