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Security Detection Framework for Smart Terminals of Electric Power Internet of Things

Published:03 May 2024Publication History

ABSTRACT

As Internet of Things (IoT) technology and power industry production become more closely integrated, more and more power IoT smart terminals are playing an important role in power production. However, due to the specialized nature of IoT security, enterprise users cannot fully understand the security risks and vulnerabilities of power IoT smart terminals, and cannot meet a large number of security assessment needs. Based on the main security risks of power IoT smart terminals, the firmware is tested and analyzed to detect conventional vulnerabilities, hard-coded passwords, potential security risks, etc.; fuzzy testing, remote scanning, and other strategies are used to achieve the vulnerability mining test for online devices of power IoT smart terminals. The experimental results show that the research can effectively test the firmware security of power IoT smart terminals and perform vulnerability mining tests for online devices, which meets the enterprise security requirements for power IoT smart terminals.

References

  1. Hui H, Ding Y, Song Y. Adaptive time-delay control of flexible loads in power systems facing accidental outages[J]. Applied Energy, 2020, 275: 115321.Google ScholarGoogle ScholarCross RefCross Ref
  2. Calabresi G. The cost of accidents: a legal and economic analysis[M]. Yale University Press, 2008..Google ScholarGoogle Scholar
  3. Xie H, Jiang M, Zhang D, IntelliSense technology in the new power systems[J]. Renewable and Sustainable Energy Reviews, 2023, 177: 113229.Google ScholarGoogle ScholarCross RefCross Ref
  4. Sridhar S, Hahn A, Govindarasu M. Cyber–physical system security for the electric power grid[J]. Proceedings of the IEEE, 2011, 100(1): 210-224.Google ScholarGoogle ScholarCross RefCross Ref
  5. Ghiasi M, Dehghani M, Niknam T, Resiliency/cost-based optimal design of distribution network to maintain power system stability against physical attacks: A practical study case[J]. IEEE Access, 2021, 9: 43862-43875.Google ScholarGoogle ScholarCross RefCross Ref
  6. Makrakis G M, Kolias C, Kambourakis G, Industrial and critical infrastructure security: Technical analysis of real-life security incidents[J]. Ieee Access, 2021, 9: 165295-165325.Google ScholarGoogle ScholarCross RefCross Ref
  7. Wang Q, Tai W, Tang Y, Review of the false data injection attack against the cyber‐physical power system[J]. IET Cyber‐Physical Systems: Theory & Applications, 2019, 4(2): 101-107.Google ScholarGoogle Scholar
  8. Li Y, Tu W. Traffic modelling for IoT networks: A survey[C]//Proceedings of the 10th International Conference on Information Communication and Management. 2020: 4-9.Google ScholarGoogle Scholar
  9. Wang Y, Lin X, Wu J, Contrastive GNN-based Traffic Anomaly Analysis Against Imbalanced Dataset in IoT-based ITS[C]//GLOBECOM 2022-2022 IEEE Global Communications Conference. IEEE, 2022: 3557-3562.Google ScholarGoogle Scholar
  10. Wu S, Mao W, Li G, IoT based cloud monitoring system for high-voltage power distribution room in the electric substation[C]//Journal of Physics: Conference Series. IOP Publishing, 2020, 1684(1): 012144.Google ScholarGoogle ScholarCross RefCross Ref
  11. Wu Y, Dai H N, Tang H. Graph neural networks for anomaly detection in industrial internet of things[J]. IEEE Internet of Things Journal, 2021, 9(12): 9214-9231.Google ScholarGoogle ScholarCross RefCross Ref

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              IoTAAI '23: Proceedings of the 2023 5th International Conference on Internet of Things, Automation and Artificial Intelligence
              November 2023
              902 pages
              ISBN:9798400716485
              DOI:10.1145/3653081

              Copyright © 2023 ACM

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              Publication History

              • Published: 3 May 2024

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