Abstract
This paper discusses several issues of evaluation and comparison of anomaly detection algorithms, namely lack of publicly available implementations and annotated data sets. Another problem of many methods is a detection delay caused by operating on data binned to a long time intervals. The paper presents a library under development which aims to tackle the comparison and evaluation issues. Further, the paper proposes a novel anomaly detection approach that can contribute to anomaly detection in real-time. © 2012 IFIP International Federation for Information Processing.
Cite
CITATION STYLE
Bartoš, V., & Žádník, M. (2012). Network anomaly detection: Comparison and real-time issues. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7279 LNCS, pp. 118–121). https://doi.org/10.1007/978-3-642-30633-4_15
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