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A Component Vulnerability Matching Approach for IoT Firmware

Published:07 November 2023Publication History

ABSTRACT

Component vulnerability matching offers an approach for discovering vulnerabilities existing in IoT firmware. In this work, A component composition analysis and reliability assessment (C2ARA) is developed to improve the component vulnerability matching. The C2ARA method employs a knowledge graph for discovering the components and their relationships from the extracted file system of the firmware. The key to the proposed method is to discover vulnerabilities from the component composition extracted from IoT firmware file systems, rather than only the information provided by CVE databases and firmware vendor. The results of the experiment with a large-scale dataset demonstrate the effectiveness of the C2ARA method.

References

  1. [1]David Y, Partush N, and Yahav E. 2018. Firmup: Precise static detection of common vulnerabilities in firmware. ACM SIGPLAN Notices, 53(2), 392-404.Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. [2]Hou J, Li T, and Chang C. 2017. Research for vulnerability detection of embedded system firmware. Procedia Computer Science, 107, 814-818.Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. [3]Yao Y, Zhou W, Jia Y, et al. Identifying privilege separation vulnerabilities in IoT firmware with symbolic execution[C]//European Symposium on Research in Computer Security. Springer, Cham, 2019: 638-657.Google ScholarGoogle Scholar
  4. [4]He D, Yu X, Li T, et al. Firmware Vulnerabilities Homology Detection Based on Clonal Selection Algorithm for IoT Devices[J]. IEEE Internet of Things Journal, 2022.Google ScholarGoogle ScholarCross RefCross Ref

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  1. A Component Vulnerability Matching Approach for IoT Firmware

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      cover image ACM Other conferences
      APNet '22: Proceedings of the 6th Asia-Pacific Workshop on Networking
      July 2022
      110 pages
      ISBN:9781450397483
      DOI:10.1145/3542637

      Copyright © 2022 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 7 November 2023

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