Geometry and Topology for Data

Geometry and Topology for Data

2016

Computer Science majors Erin Taylor and Ian Frankenburg, along with Math major Eric Peshkin, spent ten weeks understanding how geometry and topology, in tandem with statistics and machine-learning, can aid in quantifying anomalous behavior in cyber-networks. The team was sponsored by Geometric Data Anaytics, Inc., and used real anonymized Netflow data provided by Duke’s Information Technology Security Office.

The team produced features measuring cyber-behavior at the node, aggregate node, edge, and subnetwork level. Using both Python and MATLAB, they constructed tools that enabled the fitting of probabilistic models to sets of these features, and built visualization devices for these models.

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Client

Project Manager

  • Joe Marion, Statistics

Participants

Related People

Mathematics

Mathematics

Computer Science

Computer Science