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Standardized container virtualization approach for collecting host intrusion detection data

Röhling Martin Max, Grimmer Martin, Kreußel Dennis, Hoffmann Jörn, Franczyk Bogdan

Annals of Computer Science and Information Systems

2019

Vol. 18

459--463

Anomaly-based Intrusion Detection Systems (IDS) can be instrumental in detecting attacks on IT systems. For evaluation and training of IDS, data sets containing samples of common security-scenarios are essential. Existing data sets are not sufficient for training modern IDS. This work introduces a new methodology for recording data that is useful in the context of intrusion detection. The approach presented is comprised of a system architecture as well as a novel framework for simulating security-related scenarios.