GDA is pioneering shape analytics for cyber-defense. Our typical pipeline involves extracting shape-based features from cyber data and integrating them within machine-learning and statistical tools. We complement your workflow by contributing to the efficiency and accuracy of your security professionals.

Our analytic methods include:

  • MCMC
  • Switchpoint detection
  • Machine learning
  • Spectral Graph theory
  • Model Selection
  • Network Statistics

Our domains of expertise include:

  • Insider threat detection
  • Quantifying normal network operations
  • Intrusion detection and prevention
  • Advanced Persistent Threats
  • Netflow, PCAP
  • System Logs
  • Splunk

GDA projects related to cyber-defense have been funded by OSD and LAS in collaboration with APL and Draper Labs.