A Survey on Network Anomaly Detection
International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)
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Networks of various kinds often experience anomalous behavior. Examples include attacks or large data transfers in IP networks, presence of intruders in distributed video surveillance systems, and an automobile accident or an untimely congestion in a road network. System administrators can attempt to prevent such attacks using intrusion detection tools and systems. There are many commercially available Intrusion Detection Systems (IDSs). However, most IDSs lack the capability to detect novel or previously unknown attacks. A special type of IDSs, called Anomaly Detection Systems, develop models based on normal system or network behavior, with the goal of detecting both known and unknown attacks. Anomaly detection systems face many problems including high rate of false alarm, ability to work in online mode, and scalability. This paper presents a selective survey of incremental approaches for detecting anomaly in normal system or network traffic.
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Anomaly Detection, Incremental, Attack, Clustering.