Scholarlink

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.

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Embedded Anomaly Detection System for In-Vehicle Networking Cybersecurity

  • 会议论文

  • 发表日期：

    2025年

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  • Sara Visconti,
  • Ettore Soldaini,
  • Pierpaolo Dini,
  • Abdussalam Elhanashi,
  • Sergio Saponara

摘要

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.