A journal of IEEE and CAA , publishes
high-quality papers in English on original
theoretical/experimental research
and development in all areas of automation
Volume 10
Issue 2
IEEE/CAA Journal of Automatica Sinica
| Citation: | Z. Y. Zhang, Y. Qin, J. P. Wang, H. Li, and R. L. Deng, “Detecting the one-shot dummy attack on the power industrial control processes with an unsupervised data-driven approach,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 550–553, Feb. 2023. doi: 10.1109/JAS.2023.123243
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| [1] |
W. Duo, M. Zhou, and A. Abusorrah, “A survey of cyber attacks on cyber physical systems: Recent advances and challenges,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 5, pp. 784–800, Apr. 2022. doi: 10.1109/JAS.2022.105548
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| [2] |
Y. Liu, P. Ning, and M. K. Reiter, “False data injection attacks against state estimation in electric power grids,” ACM Trans. Inform. Syst. Security, vol. 14, no. 1, pp. 1–33, May 2011.
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| [3] |
X. Liu, Y. Song, and Z. Li, “Dummy data attacks in power systems,” IEEE Trans. Smart Grid, vol. 11, no. 2, pp. 1792–1795, Mar. 2020. doi: 10.1109/TSG.2019.2929702
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| [4] |
A. S. Musleh, G. Chen, and Z.-Y. Dong, “A survey on the detection algorithms for false data injection attacks in smart grids,” IEEE Trans. Smart Grid, vol. 11, no. 3, pp. 2218–2234, May 2020. doi: 10.1109/TSG.2019.2949998
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| [5] |
X. Liu, Z. Li, and Z. Li, “Optimal protection strategy against false data injection attacks in power systems,” IEEE Trans. Smart Grid, vol. 8, no. 4, pp. 1802–1810, Jul. 2017. doi: 10.1109/TSG.2015.2508449
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| [6] |
Z. Zhang, R. Deng,D. K. Yau, et al., “Analysis of moving target defense against false data injection attacks on power grid,” IEEE Trans. Inform. Forens. Secur., vol. 15, no. 1, pp. 2320–2335, Feb. 2020.
|
| [7] |
S. Peng, M. Sun, and Z. Zhang, “Application of machine learning in cyber security of cyber-physical power systems,” Automation Electric Power Syst., vol. 46, no. 9, pp. 200–215, Sept. 2022.
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| [8] |
J. Zhang, L. Pan, Q.-L. Han, C. Chen, S. Wen, and Y. Xiang, “Deep learning based attack detection for cyber-physical system cybersecurity: A survey,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 377–391, Mar. 2022. doi: 10.1109/JAS.2021.1004261
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| [9] |
G. Chaojun, P. Jirutitijaroen, and M. Motani, “Detecting false data injection attacks in AC state estimation,” IEEE Trans. Smart Grid, vol. 6, no. 5, pp. 2476–2483, Sept. 2015. doi: 10.1109/TSG.2015.2388545
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| [10] |
A. S. Musleh, M. Debouza, H. M. Khalid, and A. Al-Durra, “Detection of false data injection attacks in smart grids: A real-time principle component analysis,” in Proc. 45th Annu. Conf. IEEE Ind. Electron. Soc., 2019, pp. 2958−2963.
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| [11] |
M. M. Breunig, H.-P. Kriegel, R. T. Ng, and J. Sander, “LOF: Identifying density-based local outliers,” ACM Sigmod Record, vol. 29, no. 2, pp. 93–104, Jun. 2000. doi: 10.1145/335191.335388
|
| [12] |
J. Tang, Z. Chen, A. W.Fu, and D. W. Cheung, “Enhancing effectiveness of outlier detections for low density patterns,” in Proc. Pacific-Asia Conf. Knowledge Discovery Data Mining, 2002, pp. 535−548.
|
| [13] |
K. Zhang, M. Hutter, and H. Jin, “A new local distance-based outlier detection approach for scattered real-world data,” in Proc. Pacific-Asia Conf. Knowledge Discovery Data Mining, 2009, pp. 813−822.
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