Robust PCA for Anomaly Detection in Cyber Networks

@article{Paffenroth2018RobustPF,
  title={Robust PCA for Anomaly Detection in Cyber Networks},
  author={Randy Paffenroth and Kathleen M Kay and Leslie D. Servi},
  journal={CoRR},
  year={2018},
  volume={abs/1801.01571}
}
This paper uses network packet capture data to demonstrate how Robust Principal Component Analysis (RPCA) can be used in a new way to detect anomalies which serve as cyber-network attack indicators. The approach requires only a few parameters to be learned using partitioned training data and shows promise of ameliorating the need for an exhaustive set of examples of different types of network attacks. For Lincoln Labs DARPA intrusion detection data set, the method achieves low false-positive… CONTINUE READING
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