Optimal Attack Energy Allocation against Remote State Estimation
Recently, the security issue of wireless cyber-physical systems (CPS) has attracted much attention from different communities. In this paper, we consider energy-efficient optimal attack power schedule against remote state estimation of wireless CPS under constrained denial-of-service attacks based o...
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| Published in | IEEE transactions on automatic control Vol. 63; no. 7; pp. 2199 - 2205 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
IEEE
01.07.2018
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0018-9286 1558-2523 |
| DOI | 10.1109/TAC.2017.2775344 |
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| Abstract | Recently, the security issue of wireless cyber-physical systems (CPS) has attracted much attention from different communities. In this paper, we consider energy-efficient optimal attack power schedule against remote state estimation of wireless CPS under constrained denial-of-service attacks based on channels' signal-to-interference-plus-noise ratio (SINR). We propose a wireless communication model with SINRs of channels, in which different attack powers can cause different dropout rates. The problem of optimal attack power schedule that causes the largest performance degradation of the remote state estimation, subject to attacker's average energy constraint in multisystems, is solved by formulating it as a Markov decision process. We show that an optimal deterministic and stationary policy exists and the optimal policy has a threshold structure. |
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| AbstractList | Recently, the security issue of wireless cyber-physical systems (CPS) has attracted much attention from different communities. In this paper, we consider energy-efficient optimal attack power schedule against remote state estimation of wireless CPS under constrained denial-of-service attacks based on channels' signal-to-interference-plus-noise ratio (SINR). We propose a wireless communication model with SINRs of channels, in which different attack powers can cause different dropout rates. The problem of optimal attack power schedule that causes the largest performance degradation of the remote state estimation, subject to attacker's average energy constraint in multisystems, is solved by formulating it as a Markov decision process. We show that an optimal deterministic and stationary policy exists and the optimal policy has a threshold structure. |
| Author | Sun, Changyin Shi, Ling Cao, Xianghui Peng, Lianghong |
| Author_xml | – sequence: 1 givenname: Lianghong orcidid: 0000-0003-0074-5953 surname: Peng fullname: Peng, Lianghong email: lhpeng@seu.edu.cn organization: Southeast University, Nanjing, China – sequence: 2 givenname: Ling orcidid: 0000-0002-6771-8258 surname: Shi fullname: Shi, Ling email: eesling@ust.hk organization: Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Kowloon, Hong Kong – sequence: 3 givenname: Xianghui orcidid: 0000-0002-6771-0571 surname: Cao fullname: Cao, Xianghui email: xhcao@seu.edu.cn organization: Southeast University, Nanjing, China – sequence: 4 givenname: Changyin orcidid: 0000-0001-9269-334X surname: Sun fullname: Sun, Changyin email: cysun@seu.edu.cn organization: Southeast University, Nanjing, China |
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| Cites_doi | 10.1109/JPROC.2011.2161428 10.1109/TAC.2015.2409905 10.1239/jap/1152413725 10.1109/JIOT.2016.2516102 10.1016/j.automatica.2014.10.067 10.1145/2076569.2076581 10.1016/j.automatica.2011.02.037 10.1109/TCNS.2016.2549640 10.1007/978-3-319-42836-9_29 10.1109/TSP.2013.2283838 10.1109/TII.2015.2499123 10.1201/b13595 10.1109/ICIP.2004.1421364 10.1109/TAC.2014.2322153 10.1109/MC.2002.1039518 |
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| SubjectTerms | Cyber-physical systems (CPS) Interference Jamming Kalman filtering Markov processes optimization algorithms Sensors Signal to noise ratio State estimation Wireless communication Wireless sensor networks |
| Title | Optimal Attack Energy Allocation against Remote State Estimation |
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