Securing AI-driven platform engineering: Integrating machine learning with proactive cyber defense

Modern platform engineering environments face rapidly evolving cyber threats that traditional security tools cannot detect in real time. This talk presents a practical approach to integrating AI and machine learning into platform security architectures to enable intelligent threat detection, anomaly identification, and automated response across cloud-native and CI/CD platforms. Attendees will learn how ML models can analyze telemetry, behavioral patterns, and infrastructure signals to proactively identify attacks, reduce false positives, and strengthen security without slowing developer workflows. The session provides a clear blueprint for building AI-driven, security-by-design platforms that improve resilience, scalability, and operational efficiency.