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A Survey on Data Mining Approaches for Network Intrusion Detection System
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 159 - Number 1 |
| Year of Publication: 2017 |
| Authors: Anirudha A. Kolpyakwar, Mangesh G. Ingle, Ritesh V. Deshmukh |
10.5120/ijca2017912615
|
Anirudha A. Kolpyakwar, Mangesh G. Ingle, Ritesh V. Deshmukh . A Survey on Data Mining Approaches for Network Intrusion Detection System. International Journal of Computer Applications. 159, 1 ( Feb 2017), 20-23. DOI=10.5120/ijca2017912615
Abstract
Data mining has been gaining popularity in knowledge discovery field, particularity with the increasing availability of digital documents in various languages from all around the world. Network intrusion detection is the process of monitoring the events occurring in a computing system or network and analysing them for signs of intrusions. In this paper, intrusion detection & several areas of intrusion detection in which data mining technology applied are discussed. Data mining techniques are used to discover consistent and useful patterns of system features that describe program and user behaviour. Data mining can improve variant detection rate, control false alarm rate and reduce false dismissals. By using these set of relevant system features to compute classifiers that recognize anomalies & known intrusion.
References
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