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INTERSTICE - INTelligent sEcuRity SoluTIons for Connected vEhicles
The changing landscape of connected vehicles presents major cybersecurity challenges. The project develops a system based on machine learning for intrusion detection in vehicle networks such as CAN and Automotive Ethernet. The system monitors and analyzes data traffic to quickly identify threats and apply mitigation strategies.
The project is a collaboration between Scania CV, RISE and Scaleout Systems. This project aims to contribute to the development of a machine learning-driven onboard intrusion detection system for in-vehicle communication networks, project introduces: (a) Innovative methods for generating attack data using advanced simulation environments and generative AI models. (b) Tools and methods for analyzing network data and solutions for complex attack detection on CAN and Automotive Ethernet, based on ML models with an emphasis on transparency and trustworthiness by integrating explainability. (c) Effective strategies for deploying lightweight IDS on embedded systems, such as vehicle ECUs, and federated learning-based solutions to develop the vehicle's aggregated IDS model.
Summary
Project name
INTERSTICE
Status
Active
RISE role in project
Deltagare
Project start
Duration
2 år
Total budget
2 710 169 SEK