Synthetic dataset generator for anomaly detection in a university environment
This article introduces a recently developed synthetic dataset generator, which contains anonymised data from the Prague University of Economics and Business information system logs. The generator is opensource and is able to scale this data time-wise and also perform injection of the data with cybe...
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Veröffentlicht in: | Intelligent data analysis 2023-01, Vol.27 (2), p.417-422 |
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Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | This article introduces a recently developed synthetic dataset generator, which contains anonymised data from the Prague University of Economics and Business information system logs. The generator is opensource and is able to scale this data time-wise and also perform injection of the data with cyberattackers’ behaviour patterns. The anonymised data still contains user behaviour patterns; therefore, individual anomalous behaviour can be detected. Different types of real attack behaviour patterns in the university environment have been selected; they are used to demonstrate attackers’ behaviour in synthetically created system logs. The mentioned features allow other researchers to benchmark their anomaly detection algorithms with complex data. |
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ISSN: | 1088-467X 1571-4128 |
DOI: | 10.3233/IDA-216511 |