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Information and Infrastructure Integrity Initiative

Machine Learning String Tools for Operational and Network Security

Principal Investigator: C Oehmen
Technical Advisor: G Fink, Adaptive Systems Focus Area

Purpose of research

  • Provide capability framework for rapidly developing new text-based characterization applications in cyber domains
  • Provide a pattern-matching approach to complement or augment current rule-based approaches in cybersecurity

Key idea

Digital data is analogous to biological sequences. Let's exploit biosequence theory to provide rigorous and repeatable framework to augment cybersecurity.

Discriminator

Discriminator for this R&D is that it does not rely on rule-based approaches. This approach enables more rapid evolution of defense strategies to help keep pace with evolving threat.

Summary

Machine Learning String Tools for Operational and Network Security (MLSTONES) is a collection of methods for characterizing text-based strings from various cyber applications using biological sequence analysis theory and machine learning to extract patterns.

Project Management

Projects