Applied Mathematics and Nonlinear Sciences (Jan 2024)

UEFI-based Research on the Inner Operation Mechanism and Characteristics of Firmware Vulnerabilities in Key Devices of Electric Power Monitoring Systems

  • Chen Mingliang,
  • Yu Yingting,
  • Xie Guoqiang,
  • Zeng Chuanhan,
  • Xu Zaide

DOI
https://doi.org/10.2478/amns-2024-0136
Journal volume & issue
Vol. 9, no. 1

Abstract

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With the large number of computer technology and modern communication technology used in power monitoring systems, its security protection is constantly facing new challenges. The UEFI firmware is used to construct the physical connection structure of key devices in the power monitoring system in this paper. Using fuzzy testing methods to mine the vulnerabilities existing in the power monitoring system by generating a large number of variant test cases as the monitoring object, based on the collection of information of the basic blocks covered during the test run of the vulnerability seed to determine the target point to which the seed belongs. The coverage weight of the seed is determined with the help of the simulated annealing algorithm in order to accomplish task division of the target point. The fuzzy test method is used to analyze the operation mechanism and characteristics of the vulnerabilities in the power monitoring system, and the firmware attack mechanism of different HOOKs under UEFI is explored to summarize the characteristics of the scenarios in which the vulnerabilities appear in the power system as well as their impacts. The results show that the impact caused by vulnerabilities in the power monitoring system on the generation side and transmission side is mainly to damage the integrity and availability of information, the integrity and availability of the vulnerabilities in the generation side of the production side of the device with a risk rating of 63.74, 71.73, respectively, and the vulnerabilities in the transmission side of the SCADA with a risk rating of 79.04, 69.36, respectively. The vulnerabilities detected 608 security vulnerabilities were implanted in the UEF module, and 653 possible security problems were reported by the detection, of which the statistical underreporting rate was 1.48% and the false alarm rate was 9.05%.

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