TY - GEN
T1 - A Time-Stamp Attack on Digital Twin-Based Lithium-ion Battery Monitoring for Electric Vehicles
AU - Pooyandeh, Mitra
AU - Sohn, Insoo
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Digital twin technology plays a crucial role in accurately estimating the State of Charge (SoC) for Lithiumion Batteries (LIBs) in the field of electric vehicles. These digital replicas provide real-Time insights into LIB behavior, enabling predictive maintenance and ensuring vehicle performance and safety. However, the security of digital twin-based LIB monitoring systems has become a critical concern, despite their numerous benefits. This study delves into the security aspect of digital twin technology, focusing on the vulnerability of SoC estimation to timestamp attacks. These covert attacks disrupt the chronological order of data packets, casting a shadow on the integrity and accuracy of LIB state predictions. This research aims to shed light on the disruptive capability of timestamp attacks, emphasizing the need for robust defense mechanisms to safeguard the integrity of EV battery data and the reliability of prediction models.
AB - Digital twin technology plays a crucial role in accurately estimating the State of Charge (SoC) for Lithiumion Batteries (LIBs) in the field of electric vehicles. These digital replicas provide real-Time insights into LIB behavior, enabling predictive maintenance and ensuring vehicle performance and safety. However, the security of digital twin-based LIB monitoring systems has become a critical concern, despite their numerous benefits. This study delves into the security aspect of digital twin technology, focusing on the vulnerability of SoC estimation to timestamp attacks. These covert attacks disrupt the chronological order of data packets, casting a shadow on the integrity and accuracy of LIB state predictions. This research aims to shed light on the disruptive capability of timestamp attacks, emphasizing the need for robust defense mechanisms to safeguard the integrity of EV battery data and the reliability of prediction models.
KW - Digital Twin
KW - Lithium-ion Batteries(LIBs)
KW - Security
KW - Time-Stamp Attack
UR - http://www.scopus.com/inward/record.url?scp=85189943859&partnerID=8YFLogxK
U2 - 10.1109/ICAIIC60209.2024.10463501
DO - 10.1109/ICAIIC60209.2024.10463501
M3 - Conference contribution
AN - SCOPUS:85189943859
T3 - 6th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2024
SP - 499
EP - 502
BT - 6th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2024
Y2 - 19 February 2024 through 22 February 2024
ER -