TY - GEN
T1 - Acceleration Consistency Analysis Based GNSS Spoofing Detection for Autonomous Vehicles
AU - Zhang, Cheng
AU - Wang, Hongmei
AU - Hu, Hongxing
AU - Wang, Shouwei
AU - Liu, Hong
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Global Navigation Satellite System (GNSS) positioning technology has been widely applied in Autonomous Vehicles (AVs), but these AVs suffer from potential security threats of GNSS spoofing attacks. This work proposes a GNSS spoofing detection algorithm for AVs. The algorithm checks the consistency of two acceleration series deceived from GNSS and IMU to detect GNSS spoofing. Ideally, the two acceleration series are consistent in normal conditions and inconsistent under spoofing. However, measurement noise and outliers may cause inconsistency even in normal conditions, which will produce false alarms. Thus, the work also develops a method to analyze acceleration series in the frequency domain and find frequency components that really have benefits to consistency checking. As a result, the algorithm can obtain a high detection accuracy and a low false alarm rate simultaneously in all attack scenarios proposed in the work.
AB - Global Navigation Satellite System (GNSS) positioning technology has been widely applied in Autonomous Vehicles (AVs), but these AVs suffer from potential security threats of GNSS spoofing attacks. This work proposes a GNSS spoofing detection algorithm for AVs. The algorithm checks the consistency of two acceleration series deceived from GNSS and IMU to detect GNSS spoofing. Ideally, the two acceleration series are consistent in normal conditions and inconsistent under spoofing. However, measurement noise and outliers may cause inconsistency even in normal conditions, which will produce false alarms. Thus, the work also develops a method to analyze acceleration series in the frequency domain and find frequency components that really have benefits to consistency checking. As a result, the algorithm can obtain a high detection accuracy and a low false alarm rate simultaneously in all attack scenarios proposed in the work.
KW - GNSS spoofing detection
KW - autonomous vehicle
KW - component
KW - frequency domain analysis
KW - time series analysis
UR - https://www.scopus.com/pages/publications/85163187621
U2 - 10.1109/ICCECE58074.2023.10135427
DO - 10.1109/ICCECE58074.2023.10135427
M3 - 会议稿件
AN - SCOPUS:85163187621
T3 - 2023 3rd International Conference on Consumer Electronics and Computer Engineering, ICCECE 2023
SP - 66
EP - 72
BT - 2023 3rd International Conference on Consumer Electronics and Computer Engineering, ICCECE 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd International Conference on Consumer Electronics and Computer Engineering, ICCECE 2023
Y2 - 6 January 2023 through 8 January 2023
ER -