Imagine cars talking to each other and traffic lights to avoid crashes, but they don't know if the other car is lying or hacked. This system acts like a digital background check that happens in milliseconds. It ensures every piece of data comes from a verified source before the car decides to brake or turn.
Autonomous vehicles cannot safely cooperate if they cannot verify that the data received from other cars or infrastructure is honest and untampered. This lack of trust prevents the full deployment of safety-critical automated driving functions.
A Trust Assessment Framework (TAF) for quantifying trust using runtime evidence and a 'chip-to-cloud' security chain using Trusted Execution Environments.
If you are an OEM dealing with the risk of malicious data causing accidents — this project developed a Trust Assessment Framework that verifies the identity and integrity of other vehicles. This ensures safety-critical functions like intersection movement assist are based on honest data.
If you are a provider dealing with insecure data hand-offs between vehicles and the cloud — this project developed a chip-to-cloud chain of trust. This allows you to offer secure Multi-Access Edge Computing (MEC) services for fleet management.
If you are a fleet operator dealing with coordination errors in automated routing — this project developed a system for continuous authorization and authentication. This reduces risks when outsourcing tasks to the cloud for cooperative routing and parking.
Based on available project data, specific pricing or cost structures are not provided.
Yes, the project established a trust plane across vehicles, central clouds, and Multi-Access Edge Computing (MEC) environments to extend operational boundaries.
Based on available project data, specific licensing terms are not mentioned.
It uses hardware-based Roots of Trust (RoTs) and Trusted Execution Environments (TEEs) to create a verifiable chain of trust from the chip to the cloud.
The project period runs from 2022-09-01 to 2025-08-31, indicating it is currently in its final stages of development.
The project is heavily industry-driven with a 59% industry ratio, comprising 10 companies and 6 SMEs across 9 countries. This high level of commercial involvement, combined with 4 universities and 3 research centers, suggests the results are designed for practical market application rather than pure academic study.
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