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Automated vehicles and connected vehicles are connected within themselves and outside using different technologies. However, because of their larger attack surfaces, modern vehicles’ increasing capability and connectivity also make them more susceptible to cyberattacks that target both internal and external networks. Machine learning algorithms can be used to create an intrusion detection system. The system utilizes algorithms including decision tree, random forest, extra trees, cluster labeling (CL) K-means, and extreme gradient boosting (XGBoost). An intrusion detection system is created to identify both known and unknown attacks.

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*MTH-IDS—A Multi-tiered Hybrid Intrusion Detection System for Internet of Vehicle

  • 会议论文

  • 发表日期：

    2026年

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  • S. Rama Devi,
  • Hanshitha Vallem,
  • Snigdha Chokkarapu,
  • Jessica Hazel,
  • Akanksha Badrapu

摘要

Automated vehicles and connected vehicles are connected within themselves and outside using different technologies. However, because of their larger attack surfaces, modern vehicles’ increasing capability and connectivity also make them more susceptible to cyberattacks that target both internal and external networks. Machine learning algorithms can be used to create an intrusion detection system. The system utilizes algorithms including decision tree, random forest, extra trees, cluster labeling (CL) K-means, and extreme gradient boosting (XGBoost). An intrusion detection system is created to identify both known and unknown attacks.