The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Distributed Attack Detection and Secure Estimation of Networked Cyber-Physical Systems Against False Data Injection Attacks and Jamming Attacks
Open accessAbstract
This paper is concerned with the problem of joint distributed attack detection and distributed secure estimation for a networked cyber-physical system under physical and cyber attacks. The system is monitored by a wireless sensor network, in which a group of sensors is spatially distributed and the sensors' measurements are broadcast to remote estimators via a wireless network medium. A malicious adversary simultaneously launches a false data injection attack at the physical system layer to intentionally modify the system's state and jamming attacks at the cyber layer to block the wireless transmission channels between sensors and remote estimators. The sensors' measurements can be randomly dropped with mathematical probability if the corresponding transmission channels are deliberately jammed by the adversary. Resilient attack detection estimators are delicately constructed to provide locally reliable state estimations and detect the false data injection attack. Then, criteria for analyzing the estimation performance and designing the desired estimators are derived to guarantee the solvability of the problem. Finally, the effectiveness of the proposed approach is shown through an illustrative example.
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Cites
Diagnosis and Fault-Tolerant Control
Blanke, M., Kinnaert, M., Lunze, J., & Staroswiecki, M. (2003) · Springer eBooks · doi:10.1007/978-3-662-05344-7 · Cited by 2,789
False data injection attacks against state estimation in electric power grids
Liu, Y., Ning, P., & Reiter, M. K. (2011) · ACM Transactions on Information and System Security · doi:10.1145/1952982.1952995 · Cited by 2,428
Attack Detection and Identification in Cyber-Physical Systems
Pasqualetti, F., Dorfler, F., & Bullo, F. (2013) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2013.2266831 · Cited by 2,109
Experimental Security Analysis of a Modern Automobile
Koscher, K., Czeskis, A., Roesner, F., Patel, S., Kohno, T., Checkoway, S., McCoy, D., Kantor, B., Anderson, D., Shacham, H., et al. (2010) · 2010 IEEE Symposium on Security and Privacy · doi:10.1109/sp.2010.34 · Cited by 1,849
Secure Estimation and Control for Cyber-Physical Systems Under Adversarial Attacks
Fawzi, H., Tabuada, P., & Diggavi, S. (2014) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2014.2303233 · Cited by 1,278
Diagnosis and Fault-Tolerant Control
(2006) · Springer eBooks · doi:10.1007/978-3-540-35653-0 · Cited by 1,228
Network-Induced Constraints in Networked Control Systems—A Survey
Zhang, L., Gao, H., & Kaynak, O. (2013) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2012.2219540 · Cited by 1,066
Distributed networked control systems: A brief overview
Ge, X., Yang, F., & Han, Q.-L. (2017) · Information Sciences · doi:10.1016/j.ins.2015.07.047 · Cited by 679
Self-citationDetecting Integrity Attacks on SCADA Systems
Mo, Y., Chabukswar, R., & Sinopoli, B. (2014) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2013.2280899 · Cited by 630
Optimal Denial-of-Service Attack Scheduling With Energy Constraint
Zhang, H., Cheng, P., Shi, L., & Chen, J. (2015) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2015.2409905 · Cited by 601
Cited by
Networked control systems: a survey of trends and techniques
Zhang, X.-M., Han, Q.-L., Ge, X., Ding, D., Ding, L., Yue, D., & Peng, C. (2020) · IEEE/CAA Journal of Automatica Sinica · doi:10.1109/jas.2019.1911651 · Cited by 959
Self-citationA survey on recent advances in distributed sampled-data cooperative control of multi-agent systems
Ge, X., Han, Q.-L., Ding, D., Zhang, X.-M., & Ning, B. (2018) · Neurocomputing · doi:10.1016/j.neucom.2017.10.008 · Cited by 389
Self-citationMachine Learning for DDoS Attack Detection in Industry 4.0 CPPSs
Saghezchi, F. B., Mantas, G., Violas, M. A., de Oliveira Duarte, A. M., & Rodriguez, J. (2022) · Electronics · doi:10.3390/electronics11040602 · Cited by 81
Metadata
- Authors
- Guan, Y., & Ge, X.
- Venue
- IEEE Transactions on Signal and Information Processing over Networks
- Published
- 2018-03
- Volume
- 4
- Issue
- 1
- Pages
- 48-59
- ISSN
- 2373-776X (ISSN-L)
- 2373-7778
- OpenAlex
- W2752217602
- Cited by
- 373
- References
- 24
- FWCI
- 20.83
- Type
- journal article
- Language
- en
- Open access
- green
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- Guan, Y., & Ge, X. (2018). Distributed Attack Detection and Secure Estimation of Networked Cyber-Physical Systems Against False Data Injection Attacks and Jamming Attacks. IEEE Transactions on Signal and Information Processing over Networks. https://doi.org/10.1109/tsipn.2017.2749959
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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