Survey anomaly detection in network using big data analytics
Y.S. Kalai Vani, Krishnamurthy · 2017
This survey paper focuses the architecture of an Intrusion Detection System using anomaly detection technique to find the different types of attacks in the networks in the based on the unusual behavior. This can be done by using the different set of Intrusion Detection System (IDS) which is used to detect the anomalies in the network. It applies the strategy of holding the huge amount of data in the network and the anomalies can be detected. The scheme of Big data which consists of two engines are big data processing and an analytics engine. The traditional IDS is not suitable for detecting the intrusions in a network which consists of huge amount of data. To handle this problem the new technology, big data analytics is introduced to hold the huge amount of data in the network so that any unusual behavior can be detected in the network. Many kinds of intrusions are detected by big data analytics scheme using the concept of anomaly detection which detects the unusual behavior. The analytics engine comprises a set of procedures which will detect the intrusions in the network in the form of cyber attacks types.