Comparative Study on Supervised versus Semi-supervised Machine Learning for Anomaly Detection of In-vehicle CAN Network

no code implementations • 21 Jul 2022 • Yongqi Dong, KeJia Chen, Yinxuan Peng, Zhiyuan Ma

To enhance the security of in-vehicle networks and promote the research in this area, based upon a large scale of CAN network traffic data with the extracted valuable features, this study comprehensively compared fully-supervised machine learning with semi-supervised machine learning methods for CAN message anomaly detection.

Anomaly Detection BIG-bench Machine Learning