AINS graduate specialization

Cybersecurity AI specialization

Three courses · reference 9 credits in a 36-credit stack

Cybersecurity AI connects statistical learning and orchestration to defender workflows: telemetry and anomaly detection, SOAR-style response policies with human checkpoints, and FAIR-style risk modeling with transparent assumptions.

Hands-on materials can pair with Castalia lab environments (for example ANUBIS—the Android NetHunter Unified Breach Intelligence System at anubis.castalia.institute); institution-managed ranges work equally where policy requires.

Suited for technical graduate concentrations that already include core AI, ML, and ethics.

What institutions get

  • Prioritize detections and automate responses without sacrificing auditability.
  • Quantify risk scenarios for leadership using defendable assumptions.
  • Critique adversarial and operational limits of AI in security contexts.

Courses in this cluster

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