The emergence of AI-driven autonomy in modern vehicles marks a pivotal evolution in transportation, but it also introduces deep system-level vulnerabilities that span from sensor interface tampering to compute unit compromise and untrusted communication links. Autonomous vehicles (AVs) operate as distributed intelligent systems, relying on real-time data exchange between zonal gateways, AI compute platforms, and safety-critical electronic control units (ECUs). These interactions must be protected from hardware-based attacks that could compromise functional safety, system integrity, or operational availability.
The deployment of AI-driven AVs introduces unprecedented levels of complexity. Sensors, AI compute clusters, and actuators communicate over multiple interfaces including Ethernet, PCIe, and MIPI, exposing vehicles to potential cybersecurity attacks.
This paper proposes a unified, layered hardware security architecture tailored for AI-powered automated vehicles. Grounded in current automotive Ethernet and zonal architectures, it provides end-to-end trust using hardware interface security, accelerated- cryptography, and SRAM PUF-based key provisioning. All security primitives are anchored to hardware root of trust, delivering cryptographic identity, secure boot enforcement, and trusted key storage across the entire vehicle lifecycle.