Christopher R. Harshaw

We don’t have enough information about this author to calculate their statistics. If you think this is an error let us know.
Learn More
This paper introduces a novel graph-analytic approach for detecting anomalies in network flow data called GraphPrints. Building on foundational network-mining techniques, our method represents time slices of traffic as a graph, then counts graphlets---small induced subgraphs that describe local topology. By performing outlier detection on the sequence of(More)
  • 1