Shilpi Mittal
I'm a passionate cybersecurity leader dedicated to building resilient, scalable, and future-ready security programs. With a strong focus on cloud, identity, and application security, I help organizations stay ahead of evolving threats while enabling innovation and driving business growth. I thrive at the intersection of strategy and execution, translating complex security needs into real-world solutions that empower teams, protect data, and drive business confidence.
Session
As AI-generated threats evolve—from deepfake content and synthetic identities to autonomous attack scripts—traditional security monitoring systems struggle to keep pace. This talk presents a forward-looking approach to detection engineering, tailored explicitly for synthetic threats in enterprise environments. Grounded in real-world experience with Microsoft Sentinel and MITRE ATT&CK, the session outlines techniques for modeling adversarial behavior, crafting high-fidelity analytics, and integrating automated response mechanisms.
Key focus areas include identifying machine-generated anomalies, detecting adversarial misuse of AI/ML models, and leveraging behavioral telemetry to differentiate between organic and synthetic actions. Attendees will gain practical insights into designing scalable detection rules, minimizing alert fatigue, and operationalizing threat intelligence to counter novel attack vectors. This session is designed for cloud security engineers, SOC analysts, and cyber defenders who aim to modernize their detection strategies against AI-enhanced threats.