Outside the Closed World: On Using Machine Learning for Network Intrusion Detection

@article{Sommer2010OutsideTC,
  title={Outside the Closed World: On Using Machine Learning for Network Intrusion Detection},
  author={Robin Sommer and Vern Paxson},
  journal={2010 IEEE Symposium on Security and Privacy},
  year={2010},
  pages={305-316}
}
In network intrusion detection research, one popular strategy for finding attacks is monitoring a network's activity for anomalies: deviations from profiles of normality previously learned from benign traffic, typically identified using tools borrowed from the machine learning community. [] Key Result We support this claim by identifying challenges particular to network intrusion detection, and provide a set of guidelines meant to strengthen future research on anomaly detection.

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