Ms. Kiruthika Krishnamoorthy

Automotive Cybersecurity Manager, | TRATON R&D US

Securing Learning-Enabled Motion Control in Software-Defined Vehicles

As software-defined and highly overactuated electric vehicles adopt learning-enabled components for estimation and motion control, they unlock significant performance gains—but also introduce new integrity risks. This talk explores how adversarial inputs, compromised sensors, or manipulated model updates can quietly propagate through centralized SDV architectures and impact vehicle stability, control allocation, and actuator coordination. Taking both an architectural and control perspective, the session examines how learning-based modules reshape the cyber-physical attack surface of safety-critical chassis systems. Practical overactuated vehicle examples illustrate how even bounded disturbances in learned components can influence yaw dynamics and closed-loop behavior. The discussion concludes with a layered resilience approach that combines architectural safeguards, model integrity validation, control-aware anomaly detection, and runtime safety enforcement. The goal is to enable intelligent, learning-driven motion control while preserving stability, predictability, and trust in next-generation vehicles.

Bio

Kiruthika Krishnamoorthy is a Automotive Cybersecurity Manager at TRATON R&D US, leading cybersecurity governance and compliance for motion control systems in alignment with ISO/SAE 21434 and UNECE UN R155. She oversees the development and implementation of cybersecurity artifacts across the full vehicle lifecycle, working closely with system architects, suppliers, and cross-functional teams to embed secure-by-design principles from concept through post-deployment support. Kiruthika serves on the J1939 Cybersecurity Task Force, contributing to secure communication standards for commercial vehicles. Kiruthika was also a panelist at Automotive IQ 2026, where she spoke on “How Automotive Companies Are Implementing AI-Powered Solutions to Make Cybersecurity Processes More Efficient & Robust.”. Committed to acting as an enabler of secure innovation, she focuses on strengthening threat detection and enhancing risk visibility using AI for connected and software-defined vehicles.