Anomaly extraction in backbone networks using association rules

  title={Anomaly extraction in backbone networks using association rules},
  author={Daniela Brauckhoff and Xenofontas A. Dimitropoulos and Arno Wagner and Kav{\'e} Salamatian},
  journal={IEEE/ACM Trans. Netw.},
Anomaly extraction refers to automatically finding, in a large set of flows observed during an anomalous time interval, the flows associated with the anomalous event(s). It is important for root-cause analysis, network forensics, attack mitigation, and anomaly modeling. In this paper, we use meta-data provided by several histogram-based detectors to identify suspicious flows, and then apply association rule mining to find and summarize anomalous flows. Using rich traffic data from a backbone… CONTINUE READING
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Anomaly extraction in backbone networks using association rules

  • D. Brauckhoff, X. Dimitropoulos, A. Wagner, K. Salamatian
  • TIK-Report 309, ETH Zurich, September
  • 2009
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