This work aims to implement a multi-feature intrusion detection system for the CAN bus. As vehicle technologies become more advanced, automated, and connected, their electronic systems become increasingly vulnerable to cyberattacks. To address these risks, an effective intrusion detection system is crucial. We propose combining two detection methods: Rule-based Intrusion Detection and Timing ECU Fingerprinting. This integration enhances detection capabilities by compensating for the limitations of each approach individually. Testing was conducted on an embedded board with typical automotive computational power (AURIX TC375Lite) using an experimental prototype to simulate realistic data traffic. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Embedded Anomaly Detection System for In-Vehicle Networking Cybersecurity
Visconti Sara;Ettore Soldaini;Dini Pierpaolo
;Elhanashi Abdussalam;Sergio Saponara
2024-01-01
Abstract
This work aims to implement a multi-feature intrusion detection system for the CAN bus. As vehicle technologies become more advanced, automated, and connected, their electronic systems become increasingly vulnerable to cyberattacks. To address these risks, an effective intrusion detection system is crucial. We propose combining two detection methods: Rule-based Intrusion Detection and Timing ECU Fingerprinting. This integration enhances detection capabilities by compensating for the limitations of each approach individually. Testing was conducted on an embedded board with typical automotive computational power (AURIX TC375Lite) using an experimental prototype to simulate realistic data traffic. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


