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Big Log Data Stream Processing: Adapting an Anomaly Detection Technique

Dietz, Marietheres and Pernul, Günther (2018) Big Log Data Stream Processing: Adapting an Anomaly Detection Technique. In: Hartmann, S. and Hameurlain, A. and Pernul, Günther and Wagner, R., (eds.) Database and Expert Systems Applications. DEXA 2018. Lecture Notes in Computer Science, 11030. Springer, Cham, 159^166. ISBN 978-3-319-98811-5 (print), 978-3-319-98812-2 (ebook).

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With the continuous increase in data velocity and volume nowadays, preserving system and data security is particularly affected. In order to handle the huge amount of data and to discover security incidents in real-time, analyses of log data streams are required. However, most of the log anomaly detection techniques fall short in considering continuous data processing. Thus, this paper aligns an ...


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Item type:Book section
Institutions:Business, Economics and Information Systems > Institut für Wirtschaftsinformatik > Lehrstuhl für Wirtschaftsinformatik I - Informationssysteme (Prof. Dr. Günther Pernul)
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Keywords:Data stream, Anomaly detection, Log analysis, Real-time analysis
Dewey Decimal Classification:000 Computer science, information & general works > 004 Computer science
Refereed:Yes, this version has been refereed
Created at the University of Regensburg:Yes
Item ID:38104
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