The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Detection of Faults and Attacks Including False Data Injection Attack in Smart Grid Using Kalman Filter
Abstract
By exploiting the communication infrastructure among the sensors, actuators, and control systems, attackers may compromise the security of smart-grid systems, with techniques such as denial-of-service (DoS) attack, random attack, and data-injection attack. In this paper, we present a mathematical model of the system to study these pitfalls and propose a robust security framework for the smart grid. Our framework adopts the Kalman filter to estimate the variables of a wide range of state processes in the model. The estimates from the Kalman filter and the system readings are then fed into the χ2-detector or the proposed Euclidean detector. The χ2-detector is a proven effective exploratory method used with the Kalman filter for the measurement of the relationship between dependent variables and a series of predictor variables. The χ2-detector can detect system faults/attacks, such as DoS attack, short-term, and long-term random attacks. However, the studies show that the χ2-detector is unable to detect the statistically derived false data-injection attack. To overcome this limitation, we prove that the Euclidean detector can effectively detect such a sophisticated injection attack.
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Cited by
Detecting False Data Injection Attacks in Smart Grids: A Semi-Supervised Deep Learning Approach
Zhang, Y., Wang, J., & Chen, B. (2021) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2020.3010510 · Cited by 332
Ahmad, K., Maabreh, M., Ghaly, M., Khan, K., Qadir, J., & Al-Fuqaha, A. (2022) · Computer Science Review · doi:10.1016/j.cosrev.2021.100452 · Cited by 291
State of the art of cyber-physical systems security: An automatic control perspective
Zacchia Lun, Y., D’Innocenzo, A., Smarra, F., Malavolta, I., & Di Benedetto, M. D. (2019) · Journal of Systems and Software · doi:10.1016/j.jss.2018.12.006 · Cited by 211
False data attack models, impact analyses and defense strategies in the electricity grid
Liu, X., & Li, Z. (2017) · The Electricity Journal · doi:10.1016/j.tej.2017.04.001 · Cited by 57
Stealthy Attacks against Robotic Vehicles Protected by Control-based Intrusion Detection Techniques
Dash, P., Karimibiuki, M., & Pattabiraman, K. (2021) · Digital Threats: Research and Practice · doi:10.1145/3419474 · Cited by 40
Metadata
- Authors
- Manandhar, K., Cao, X., Hu, F., & Liu, Y.
- Venue
- IEEE Transactions on Control of Network Systems
- Published
- 2014-12
- Volume
- 1
- Issue
- 4
- Pages
- 370-379
- ISSN
- 2325-5870 (ISSN-L)
- OpenAlex
- W2039984414
- Cited by
- 786
- References
- 19
- FWCI
- 24.19
- Type
- journal article
- Language
- en
- Open access
- closed
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- Manandhar, K., Cao, X., Hu, F., & Liu, Y. (2014). Detection of Faults and Attacks Including False Data Injection Attack in Smart Grid Using Kalman Filter. IEEE Transactions on Control of Network Systems. https://doi.org/10.1109/tcns.2014.2357531
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