TY - GEN
T1 - A Search-Based Approach to Identifying Jamming Attacks and Defense Policies in Wireless Networked Control
AU - Cetinkaya, Ahmet
AU - Arcaini, Paolo
AU - Ishii, Hideaki
AU - Hayakawa, Tomohisa
N1 - Funding Information:
Ahmet Cetinkaya and Paolo Arcaini are with the National Institute of Informatics, Tokyo, 101-8430, Japan cetinkaya@nii.ac.jp, arcaini@nii.ac.jp Hideaki Ishii is with the Department of Computer Science, Tokyo Insitute of Technology, Yokohama, 226-8502, Japan. ishii@c.titech.ac.jp Tomohisa Hayakawa is with the Department of Systems and Control Engineering, Tokyo Institute of Technology, Tokyo 152-8552, Japan. hayakawa@sc.e.titech.ac.jp This work is supported by JST ERATO HASUO Metamathematics for Systems Design Project (No. JPMJER1603), by JST CREST Grant No. JPMJCR15K3, and by JSPS KAKENHI under Grants 20K14771 and 18H01460.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/12/14
Y1 - 2020/12/14
N2 - State-dependent attack and defense mechanisms in a wireless networked control system are investigated. The controller in this system attempts to transmit control commands to a remotely located plant by using a wireless channel that is subject to jamming attacks from an adversary. The probability of a failure on this channel depends on the powers of both the transmission signal emitted from the controller and the jamming interference signal emitted from the attacker. We show that if the power levels of transmissions from the controller are consistently above a threshold and the average power level of the jamming interference is sufficiently small, then the networked control system is guaranteed to be almost surely asymptotically stable. However, it is hard to analytically derive optimal attack and defense policies due to the complexity of the wireless channel model. To find out potentially dangerous attacks and high-performance defense policies, we propose a search-based approach and utilize genetic algorithms. Specifically, by considering Voronoi partitions of the state space, we find attack policies that achieve large quadratic costs. We use the search-based approach also for designing defense policies, where the controller adjusts the power of the transmission signal based on the plant's state information. The efficacy of the proposed approach is demonstrated through a number of simulation-based experiments.
AB - State-dependent attack and defense mechanisms in a wireless networked control system are investigated. The controller in this system attempts to transmit control commands to a remotely located plant by using a wireless channel that is subject to jamming attacks from an adversary. The probability of a failure on this channel depends on the powers of both the transmission signal emitted from the controller and the jamming interference signal emitted from the attacker. We show that if the power levels of transmissions from the controller are consistently above a threshold and the average power level of the jamming interference is sufficiently small, then the networked control system is guaranteed to be almost surely asymptotically stable. However, it is hard to analytically derive optimal attack and defense policies due to the complexity of the wireless channel model. To find out potentially dangerous attacks and high-performance defense policies, we propose a search-based approach and utilize genetic algorithms. Specifically, by considering Voronoi partitions of the state space, we find attack policies that achieve large quadratic costs. We use the search-based approach also for designing defense policies, where the controller adjusts the power of the transmission signal based on the plant's state information. The efficacy of the proposed approach is demonstrated through a number of simulation-based experiments.
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U2 - 10.1109/CDC42340.2020.9303996
DO - 10.1109/CDC42340.2020.9303996
M3 - Conference contribution
AN - SCOPUS:85099881636
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 5717
EP - 5724
BT - 2020 59th IEEE Conference on Decision and Control, CDC 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 59th IEEE Conference on Decision and Control, CDC 2020
Y2 - 14 December 2020 through 18 December 2020
ER -