TY - GEN
T1 - Research on Vehicle Network Intrusion Detection System Based on K-means Clustering Algorithm
AU - Liu, Haotian
AU - Wei, Hongqian
AU - Zhang, Youtong
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - As the most widely used network in the vehicles, the Controller Area Network (CAN) is vulnerable to cyber-attacks due to the limitations of the bandwidth and transmission rate, lack of identity authentication, data encryption and other primary protection functions. Based on the known defects of intrusion detection systems, this paper shows a time voltage hybrid detection scheme that only relies on the physical information on the CAN bus when the data information has become unreliable. A lightweight K-means algorithm is used to train and verify the data. The test results show that the intrusion detection scheme in this paper can effectively detect the number of Electronic Control Units (ECUs) on the CAN network and play a role in checking the admission of the external ECUs connected to the bus.
AB - As the most widely used network in the vehicles, the Controller Area Network (CAN) is vulnerable to cyber-attacks due to the limitations of the bandwidth and transmission rate, lack of identity authentication, data encryption and other primary protection functions. Based on the known defects of intrusion detection systems, this paper shows a time voltage hybrid detection scheme that only relies on the physical information on the CAN bus when the data information has become unreliable. A lightweight K-means algorithm is used to train and verify the data. The test results show that the intrusion detection scheme in this paper can effectively detect the number of Electronic Control Units (ECUs) on the CAN network and play a role in checking the admission of the external ECUs connected to the bus.
KW - Controller area network
KW - Hybrid features
KW - Intelligent connected vehicle
KW - Lightweight algorithm
UR - http://www.scopus.com/inward/record.url?scp=85174540854&partnerID=8YFLogxK
U2 - 10.1109/ICSP58490.2023.10248655
DO - 10.1109/ICSP58490.2023.10248655
M3 - Conference contribution
AN - SCOPUS:85174540854
T3 - 2023 8th International Conference on Intelligent Computing and Signal Processing, ICSP 2023
SP - 44
EP - 48
BT - 2023 8th International Conference on Intelligent Computing and Signal Processing, ICSP 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th International Conference on Intelligent Computing and Signal Processing, ICSP 2023
Y2 - 21 April 2023 through 23 April 2023
ER -