Network anomaly detection research: a survey

Kurniabudi Kurniabudi, Benni Purnama, Sharipuddin Sharipuddin, Darmawijoyo Darmawijoyo, Deris Stiawan, Samsuryadi Samsuryadi, Ahmad Heryanto, Rahmat Budiarto


Data analysis to identifying attacks/anomalies is a crucial task in anomaly detection and network anomaly detection itself is an important issue in network security. Researchers have developed methods and algorithms for the improvement of the anomaly detection system. At the same time, survey papers on anomaly detection researches are available. Nevertheless, this paper attempts to analyze futher and to provide alternative taxonomy on anomaly detection researches focusing on methods, types of anomalies, data repositories, outlier identity and the most used data type. In addition, this paper summarizes information on application network categories of the existing studies.


Anomaly identity; Data type; Intrusion detection system; Network anomaly detection;

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Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
ISSN 2089-3272

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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