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2008 Communication Networks and Services Research Conference (CNSR 2008)
Critical Episode Mining in Intrusion Detection Alerts
May 05-May 08
ISBN: 978-0-7695-3135-9
One of the most important steps in attack detection using Intrusion Detection Systems (IDSs) is dealing with huge number of alerts that can be either critical single alerts and multi-step attack scenarios or false alerts and non-critical ones. In this paper we try to address the problem of managing alerts via a multi-layer alert correlation and ltering that can identify critical alerts after each step of correlation and ltering. After applying the approach on LL DDoS 1.0 data set, we achieved very good results in terms of critical alert detection rates, running time of approach and its memory usage. Our method could extract all of critical and multi-step attacksin LL DDoS 1.0 data set while we had almost 90% reduction in number of alerts.
Index Terms:
Episode mining, Critical episode, Alert mining, Attack scenario, Multistage attack
Citation:
Mahboobeh Soleimani, Ali A. Ghorbani, "Critical Episode Mining in Intrusion Detection Alerts," cnsr, pp.157-164, 2008 Communication Networks and Services Research Conference (CNSR 2008), 2008
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