Informace o publikaci

Similarity as a central approach to flow-based anomaly detection

Název česky Podobnost jako hlavní přístup k detekci anomálií na základě síťových toků
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DRAŠAR Martin VIZVÁRY Martin VYKOPAL Jan

Druh Článek v odborném periodiku
Časopis / Zdroj International Journal of Network Management
Fakulta / Pracoviště MU

Fakulta informatiky Ústav výpočetní techniky

Citace
WWW http://dx.doi.org/10.1002/nem.1867
Doi http://dx.doi.org/10.1002/nem.1867
Obor Informatika
Klíčová slova similarity; anomaly detection; network flows
Popis Network flow monitoring is currently a common practice in mid and large-size networks. Methods of flow-based anomaly detection are subject to ongoing extensive research, because detection methods based on deep packet inspection have reached their limits. However, there is a lack of comprehensive studies mapping the state of the art in this area. For this reason, we have conducted a thorough survey of flow-based anomaly detection methods published on academic conferences and used by the industry. We have analyzed these methods using the perspective of similarity which is inherent to any anomaly detection method. Based on this analysis, we have proposed a new taxonomy of network anomalies and a similarity-oriented classification of flow-based detection methods. We have also identified four issues requiring further research: the lack of flow-based evaluation data sets, infeasible benchmarking of proposed methods, excessive false positive rate, and limited coverage of certain anomaly classes.

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