Living lab for the transfer of digital health applications and AI into healthcare
Enhanced security through continuous monitoring of incidents in autonomous vehicles
For autonomous vehicles to be introduced and tested, functions, systems and services must interact reliably. During vehicle development, measures are taken at an early stage through regular testing to prevent as many security risks as possible. Particularly with the use of technologies such as artificial intelligence or connected driving, vulnerabilities and security gaps that are difficult to foresee can only be uncovered during operation.
The aim of the UNCOVER project is to develop methods and tools that record such incidents in autonomous driving functions in a systematic and structured manner. In doing so, findings from incidents in driving operations will be transferred back to model-based development. Subsequently, concepts for a re-design can be developed that consider the identified vulnerabilities and their impact on the vehicle architecture. A flexible monitoring platform is being developed to provide a tool for identification and detection that considers both cybersecurity standards and data protection aspects
UNCOVER’s approach aims to demonstrate that security risk detection and recovery response can be shortened using continuous monitoring. This is possible in particular thanks to data-based evaluation and the feedback of the results into vehicle development.
The project results are highly relevant for the German automotive industry, but can also be transferred to other safety-critical areas such as Industry 4.0, critical infrastructures or medical technology.
Victor Pazmino Betandcourt
Division: Embedded Systems and Sensors Engineering
Safety, Security and the Law
The FZI focuses in this research area on the topics of resilience for critical infrastructures, managing security, legal tech and (post-)quantum cryptography, and also deals with the mutual influence of artificial intelligence on safety and security.