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