TY - JOUR
T1 - Cybersecurity of Plug-In Electric Vehicles
T2 - Cyberattack Detection during Charging
AU - Dey, Satadru
AU - Khanra, Munmun
N1 - Publisher Copyright:
© 1982-2012 IEEE.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2021/1
Y1 - 2021/1
N2 - While large scale deployment of plug-in electric vehicles (PEVs) offers promising advantages, such as environmental benefits, energy security, and economic stability, it also poses certain cybersecurity related challenges. Unlike power grid security, PEV cybersecurity is significantly underexplored. However, cyberattacks on PEVs may lead to disastrous situations such as out-of-service EVs via denial-of-charging (DoC) or battery pack damage via overcharging. In this article, we attempt to address this issue by exploring control-oriented approaches for PEV cybersecurity. Specifically, we focus on designing algorithms for detecting cyberattacks that can potentially affect PEV battery packs during charging. We discuss two algorithms: first, static detector that utilizes only measured variables, and, second, dynamic detector that utilizes the knowledge of system dynamics along with the measurements. Furthermore, we propose a filter-based design approach for the dynamic detector that considers a multiobjective criterion including stability, robustness, and attack sensitivity. We perform theoretical analysis and simulation studies to evaluate the effectiveness of the algorithms under DoC and overcharging attacks that indicate the superiority of dynamic detector in terms of attack detectability.
AB - While large scale deployment of plug-in electric vehicles (PEVs) offers promising advantages, such as environmental benefits, energy security, and economic stability, it also poses certain cybersecurity related challenges. Unlike power grid security, PEV cybersecurity is significantly underexplored. However, cyberattacks on PEVs may lead to disastrous situations such as out-of-service EVs via denial-of-charging (DoC) or battery pack damage via overcharging. In this article, we attempt to address this issue by exploring control-oriented approaches for PEV cybersecurity. Specifically, we focus on designing algorithms for detecting cyberattacks that can potentially affect PEV battery packs during charging. We discuss two algorithms: first, static detector that utilizes only measured variables, and, second, dynamic detector that utilizes the knowledge of system dynamics along with the measurements. Furthermore, we propose a filter-based design approach for the dynamic detector that considers a multiobjective criterion including stability, robustness, and attack sensitivity. We perform theoretical analysis and simulation studies to evaluate the effectiveness of the algorithms under DoC and overcharging attacks that indicate the superiority of dynamic detector in terms of attack detectability.
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U2 - 10.1109/TIE.2020.2965497
DO - 10.1109/TIE.2020.2965497
M3 - Article
AN - SCOPUS:85084344645
VL - 68
SP - 478
EP - 487
JO - IEEE Transactions on Industrial Electronics
JF - IEEE Transactions on Industrial Electronics
SN - 0278-0046
IS - 1
M1 - 8960519
ER -