Detecting False Data Injection Attack on Cyber-Physical System Based on Delta Operator

Jianlei Gao; Senchun Chai; Min Shuai; Baihai Zhang; Linguo Cui

doi:10.23919/ChiCC.2018.8483314

Detecting False Data Injection Attack on Cyber-Physical System Based on Delta Operator

Jianlei Gao, Senchun Chai, Min Shuai, Baihai Zhang, Linguo Cui

School of Automation

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Citations (Scopus)

Abstract

More and more Cyber-Physical systems (CPSs) providing service for many critical infrastructures have been connected to the Internet, which also attracts more attention of false data injection attacks. Since CPSs require higher performance and high-speed sampling demand, it needs to discover anomalies faster and more effectively to ensure normal operation, when it has been attacked. In this paper, through studying the different discretization methods, we choose a delta operator Kalman Filter and Euclidean detector to detect the false data injection attack in sensors of CPSs and solve the problem of high-speed sampling oscillation. Besides, a false data injection attack model is designed to test and compare with related algorithm. And the result turns out that the delta operator Kalman Filter and Euclidean detector have a robust performance.

Original language	English
Title of host publication	Proceedings of the 37th Chinese Control Conference, CCC 2018
Editors	Xin Chen, Qianchuan Zhao
Publisher	IEEE Computer Society
Pages	5961-5966
Number of pages	6
ISBN (Electronic)	9789881563941
DOIs	https://doi.org/10.23919/ChiCC.2018.8483314
Publication status	Published - 5 Oct 2018
Event	37th Chinese Control Conference, CCC 2018 - Wuhan, China Duration: 25 Jul 2018 → 27 Jul 2018

Publication series

Name	Chinese Control Conference, CCC
Volume	2018-July
ISSN (Print)	1934-1768
ISSN (Electronic)	2161-2927

Conference

Conference	37th Chinese Control Conference, CCC 2018
Country/Territory	China
City	Wuhan
Period	25/07/18 → 27/07/18

Keywords

Cyber-physical systems
Delta operator Kalman Filters
Euclidean detector
False data injection attack

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10.23919/ChiCC.2018.8483314

Cite this

Gao, J., Chai, S., Shuai, M., Zhang, B., & Cui, L. (2018). Detecting False Data Injection Attack on Cyber-Physical System Based on Delta Operator. In X. Chen, & Q. Zhao (Eds.), Proceedings of the 37th Chinese Control Conference, CCC 2018 (pp. 5961-5966). Article 8483314 (Chinese Control Conference, CCC; Vol. 2018-July). IEEE Computer Society. https://doi.org/10.23919/ChiCC.2018.8483314

@inproceedings{bef29a68df294b6697d5a59951ef492b,

title = "Detecting False Data Injection Attack on Cyber-Physical System Based on Delta Operator",

abstract = "More and more Cyber-Physical systems (CPSs) providing service for many critical infrastructures have been connected to the Internet, which also attracts more attention of false data injection attacks. Since CPSs require higher performance and high-speed sampling demand, it needs to discover anomalies faster and more effectively to ensure normal operation, when it has been attacked. In this paper, through studying the different discretization methods, we choose a delta operator Kalman Filter and Euclidean detector to detect the false data injection attack in sensors of CPSs and solve the problem of high-speed sampling oscillation. Besides, a false data injection attack model is designed to test and compare with related algorithm. And the result turns out that the delta operator Kalman Filter and Euclidean detector have a robust performance.",

keywords = "Cyber-physical systems, Delta operator Kalman Filters, Euclidean detector, False data injection attack",

author = "Jianlei Gao and Senchun Chai and Min Shuai and Baihai Zhang and Linguo Cui",

note = "Publisher Copyright: {\textcopyright} 2018 Technical Committee on Control Theory, Chinese Association of Automation.; 37th Chinese Control Conference, CCC 2018 ; Conference date: 25-07-2018 Through 27-07-2018",

year = "2018",

month = oct,

day = "5",

doi = "10.23919/ChiCC.2018.8483314",

language = "English",

series = "Chinese Control Conference, CCC",

publisher = "IEEE Computer Society",

pages = "5961--5966",

editor = "Xin Chen and Qianchuan Zhao",

booktitle = "Proceedings of the 37th Chinese Control Conference, CCC 2018",

address = "United States",

}

Gao, J, Chai, S, Shuai, M, Zhang, B & Cui, L 2018, Detecting False Data Injection Attack on Cyber-Physical System Based on Delta Operator. in X Chen & Q Zhao (eds), Proceedings of the 37th Chinese Control Conference, CCC 2018., 8483314, Chinese Control Conference, CCC, vol. 2018-July, IEEE Computer Society, pp. 5961-5966, 37th Chinese Control Conference, CCC 2018, Wuhan, China, 25/07/18. https://doi.org/10.23919/ChiCC.2018.8483314

Detecting False Data Injection Attack on Cyber-Physical System Based on Delta Operator. / Gao, Jianlei; Chai, Senchun; Shuai, Min et al.
Proceedings of the 37th Chinese Control Conference, CCC 2018. ed. / Xin Chen; Qianchuan Zhao. IEEE Computer Society, 2018. p. 5961-5966 8483314 (Chinese Control Conference, CCC; Vol. 2018-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Detecting False Data Injection Attack on Cyber-Physical System Based on Delta Operator

AU - Gao, Jianlei

AU - Chai, Senchun

AU - Shuai, Min

AU - Zhang, Baihai

AU - Cui, Linguo

PY - 2018/10/5

Y1 - 2018/10/5

N2 - More and more Cyber-Physical systems (CPSs) providing service for many critical infrastructures have been connected to the Internet, which also attracts more attention of false data injection attacks. Since CPSs require higher performance and high-speed sampling demand, it needs to discover anomalies faster and more effectively to ensure normal operation, when it has been attacked. In this paper, through studying the different discretization methods, we choose a delta operator Kalman Filter and Euclidean detector to detect the false data injection attack in sensors of CPSs and solve the problem of high-speed sampling oscillation. Besides, a false data injection attack model is designed to test and compare with related algorithm. And the result turns out that the delta operator Kalman Filter and Euclidean detector have a robust performance.

AB - More and more Cyber-Physical systems (CPSs) providing service for many critical infrastructures have been connected to the Internet, which also attracts more attention of false data injection attacks. Since CPSs require higher performance and high-speed sampling demand, it needs to discover anomalies faster and more effectively to ensure normal operation, when it has been attacked. In this paper, through studying the different discretization methods, we choose a delta operator Kalman Filter and Euclidean detector to detect the false data injection attack in sensors of CPSs and solve the problem of high-speed sampling oscillation. Besides, a false data injection attack model is designed to test and compare with related algorithm. And the result turns out that the delta operator Kalman Filter and Euclidean detector have a robust performance.

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Detecting False Data Injection Attack on Cyber-Physical System Based on Delta Operator

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Keywords

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