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An Improved Fuzzy Test of Industrial Control System

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Published:24 February 2018Publication History

ABSTRACT

At present, fuzzy test is one of the most common ways of software vulnerability mining. However, the pertinence of traditional fuzzy test is not strong enough, the coverage is too low. The traditional fuzzy test can't meet the demand of the safety requirements of industrial control systems. This paper is aimed at the characteristics of industrial terminal equipment. We use genetic algorithm to design variation function and improve the memory fuzzy test to detect vulnerabilities. Based on this paper, we can effectively implement the new vulnerability mining system for industrial control system terminal, and greatly shorten the excavation time.

References

  1. Williams T. The Purdue Enterprise Reference Architecture: A Technical Guide for CIM Planning and Implementation, Instrument{M}.Research Triangle Park: Society of America,1992.Google ScholarGoogle Scholar
  2. Knapp Eric D. Industrial Network Security(Securing Critical Infrastructure Networks for Smart Grid, 245 SCADA, and Other Industrial Control Systems){M}, American: Syngress. 2011: 105--118.Google ScholarGoogle Scholar
  3. Patel S C, Graham J H, Ralston P A S, Quantitatively Assessing the Vulnerability of Critical Information Systems: A New Method for Evaluating Security Enhancements{J}. International Journal of Information Management, 2008, 28(6): 483--491. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Shuai Zhang. Safety risk analysis of industrial control system {J}. Information security and communication secrecy, 2012(3): 22--26.Google ScholarGoogle Scholar
  5. Dongyang Xu. Domestic and international industrial control system information security standards and policies and regulations introduced {J}. Automation Expo, 2013, (01): 31.Google ScholarGoogle Scholar
  6. Chen, Y. L., Wang Z.2011. Advancement of the Study on Fuzzy Testing{J}. Computer Applications and Software, 2011, 28(7); 291--293, 295.Google ScholarGoogle Scholar
  7. Berndt D J, Watkins A.2004. Investigating the performance of genetic algorithm-based software test case generation {C}//High Assurance Systems Engineering, 2004. Proceedings. Eighth IEEE International Symposium on. IEEE, 2004: 261--262. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Gu, P., 2006. Research on key technology of test case generation system based on genetic algorithm. Master's thesis, Huazhong University of Science and Technology.Google ScholarGoogle Scholar

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  1. An Improved Fuzzy Test of Industrial Control System

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      cover image ACM Other conferences
      ICCAE 2018: Proceedings of the 2018 10th International Conference on Computer and Automation Engineering
      February 2018
      260 pages
      ISBN:9781450364102
      DOI:10.1145/3192975

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 24 February 2018

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