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Vulnerability analysis of cyber physical systems under the false alarm cyber attacks

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  • Tu, Haicheng
  • Xia, Yongxiang
  • Chen, Xi

Abstract

More and more infrastructure networks have evolved into cyber physical systems (CPS). Among the previous work, CPS has developed a series of emergency mechanisms to deal with physical failures or attacks. However, the occurrence of cyber attacks, can still severely affect the normal operation of CPS. Thus, the goal of this paper is studying and analyzing the vulnerability of CPS under the cyber attacks. Taking the smart grid as a typical CPS, we consider a specific attack scenario—false alarm attack (FAA), and mathematically propose the FAA model. The attackers can inject hidden vector to make the control center mistakenly believe that links are overloaded, which further results in unnecessary power loss. Based on the FAA model, we further analyze the vulnerability of CPS under different network structures and redundant parameters. Finally, we propose a hybrid indicator, which takes the topological and electrical characteristics of links into consideration, to identify the vulnerable links in smart grid. The simulation results show that the hybrid indicator can effectively identify the vulnerable links, and has a strong correlation with the vulnerability of smart grid. Our work can provide new insights into the construction of robust CPS.

Suggested Citation

  • Tu, Haicheng & Xia, Yongxiang & Chen, Xi, 2022. "Vulnerability analysis of cyber physical systems under the false alarm cyber attacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
  • Handle: RePEc:eee:phsmap:v:599:y:2022:i:c:s0378437122003107
    DOI: 10.1016/j.physa.2022.127416
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    References listed on IDEAS

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    1. Tian, Meng & Dong, Zhengcheng & Wang, Xianpei, 2021. "Reinforcement learning approach for robustness analysis of complex networks with incomplete information," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    2. Liao, Shi-Gen & Yi, Shu-Ping, 2021. "Modeling and analysis knowledge transmission process in complex networks by considering internalization mechanism," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    3. Li, Zhenpeng & Tang, Xijin, 2019. "Robustness of complex networks to cascading failures induced by Poisson fluctuating loads," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    4. Yang, Li-xin & Long, Bin & Jiang, Jun & Liu, Xiao-Jun, 2021. "Analysis of synchronous stability and control of multiplex oscillatory power network," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    5. Deng, Yu-Jing & Li, Ya-Qian & Qin, Yu-Hua & Dong, Ming-Ru & Liu, Bin, 2020. "Optimal defense resource allocation for attacks in wireless sensor networks based on risk assessment model," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    6. Shang, Yilun, 2021. "Generalized k-cores of networks under attack with limited knowledge," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
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