Volume 48 Issue 2
Feb.  2022
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LYU Zhuo, GUO Zhimin, CHEN Cen, et al. A dynamic network threat evaluation method for smart grid embedded devices[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(2): 324-330. doi: 10.13700/j.bh.1001-5965.2020.0398(in Chinese)
Citation: LYU Zhuo, GUO Zhimin, CHEN Cen, et al. A dynamic network threat evaluation method for smart grid embedded devices[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(2): 324-330. doi: 10.13700/j.bh.1001-5965.2020.0398(in Chinese)

A dynamic network threat evaluation method for smart grid embedded devices

doi: 10.13700/j.bh.1001-5965.2020.0398
Funds:

State Grid Technology Project 5700-202024193A-0-0-00

National Natural Science Foundation of China U1736114

More Information
  • Corresponding author: LYU Zhuo, E-mail: zhuanzhuan2325@sina.com
  • Received Date: 09 Aug 2020
  • Accepted Date: 18 Dec 2020
  • Publish Date: 20 Feb 2022
  • Due to the limited computing and storage resources, the smart grid embedded devices cannot deal with the network attacks effectively and the security assessment method is weak. In order to solve these problems, a dynamic network attack behavior evaluation method for smart grid embedded devices is proposed. This method uses the security control module to analyze the communication data stream of the actual embedded device, and conduct security detection evaluation of the impact of the attack behavior in the embedded system simulator by using the component dynamic trust measurement. The final security evaluation result of the network attacks is obtained based on the whole process dynamic comprehensive measurement of the platform configuration property, the platform operation attribute and the user authentication attribute. The method is tested in the actual environment of the power distribution automation system and the power utilization information collection system. The results show that, aimed at the common attacks against the embedded devices, accuracy rate of the proposed detection method can reach more than 90%. This method provides good safety assessment accuracy, and meanwhile achieves effective upgrade of its own security.

     

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