Enhancing Security Event Management Systems with Unsupervised Anomaly Detection

@inproceedings{Goldstein2013EnhancingSE,
  title={Enhancing Security Event Management Systems with Unsupervised Anomaly Detection},
  author={Markus Goldstein and Stefan Asanger and M. Reif and A. Hutchison},
  booktitle={ICPRAM},
  year={2013}
}
  • Markus Goldstein, Stefan Asanger, +1 author A. Hutchison
  • Published in ICPRAM 2013
  • Computer Science
    • Security Information and Event Management (SIEM) systems are today a key component of complex enterprise networks. They usually aggregate and correlate events from different machines and perform a rule-based analysis to detect threats. In this paper we present an enhancement of such systems which makes use of unsupervised anomaly detection algorithms without the need for any prior training of the system. For data acquisition, events are exported from an existing SIEM appliance, parsed, unified… CONTINUE READING
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