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Microelectronics

AI-based Cyber Attack Detection for Connected Vehicles

azienda Tesi esterna in azienda    


Parole chiave CYBERSECURITY, MACHINE LEARNING, PATTERN RECOGNITION

Riferimenti LUCIANO LAVAGNO

Riferimenti esterni Michele Crepaldi, Reply Torino

Gruppi di ricerca Microelectronics

Tipo tesi APPLIED RESEARCH

Descrizione The rise of connected vehicles has increased their vulnerability to cyber attacks, which can be potentially
dangerous. To mitigate these risks, it is important to have real-time detection systems in place. The thesis
project aims to address this issue by developing a compact and efficient AI model that can detect ongoing
cyber attacks that target combustion engine operating parameters directly on the vehicle. This will
significantly improve the safety of connected vehicles by allowing for an immediate response to such threats.
The model will be optimized for the limited computational resources of the vehicle's Engine Control Unit
(ECU) to ensure its seamless integration with the vehicle's systems.

Conoscenze richieste Python programming, some knowledge of Machine Learning

Note The student will be involved in:
❑ SW and HW requirements definition
❑ Database setup: nominal engine operating conditions and attack examples
❑ Design and development of attack detection AI algorithm
❑ On edge performance optimization and miniaturization
❑ Model validation and testing (benchmarking)


Scadenza validita proposta 11/10/2024      PROPONI LA TUA CANDIDATURA




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