One of the most topical issues in the field of cybersecurity is a steady increasing numbers of successful social engineering attacks. For assessment of information system, users require the ability to assess of the intensity of user communications in social networks. However, this information is a set of linguistic variables and requires quantification. The purpose of this article is to propose approach to assignment of model parameters for estimates of the probability of multiway social engineering attack. To achieve this goal, the three different modifications of the method by Khovanov were proposed. The modifications are based on the assumption that experts could not only rank the linguistic variables, but give it rough estimates, thereby considerably empower for following quantification. Theoretical relevance of the research is a new approach to getting probability estimates from non-numeric information. Practical relevance of the research is to building a foundation for following use on the evaluation of the probability of propagation of multiway social engineering attacks and analysis of the social graph of organization employees. Thereby we lay the basis of subsequent diagnostics of information systems to identify vulnerabilities to social engineering attacks, as well as to solve social computing problems.

Original languageEnglish
Title of host publicationProceedings of 2020 23rd International Conference on Soft Computing and Measurements, SCM 2020
EditorsS. Shaposhnikov
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages37-40
Number of pages4
ISBN (Electronic)9781728196923
DOIs
StatePublished - May 2020
Event23rd International Conference on Soft Computing and Measurements, SCM 2020 - St. Petersburg, Russian Federation
Duration: 27 May 202029 May 2020

Publication series

NameProceedings of 2020 23rd International Conference on Soft Computing and Measurements, SCM 2020

Conference

Conference23rd International Conference on Soft Computing and Measurements, SCM 2020
Country/TerritoryRussian Federation
CitySt. Petersburg
Period27/05/2029/05/20

    Research areas

  • linguistic variable, probabilistic estimate, quantification, social engineering attacks, social relations analysis, user social graph

    Scopus subject areas

  • Computational Mathematics
  • Control and Optimization
  • Computer Science Applications
  • Modelling and Simulation
  • Decision Sciences (miscellaneous)
  • Instrumentation

ID: 87279194