An Approach to Quantification of Relationship Types Between Users Based on the Frequency of Combinations of Non-numeric Evaluations

  • A. KhlobystovaEmail author
  • A. Korepanova
  • A. Maksimov
  • T. Tulupyeva
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1156)


The goal of this article is to propose an approach to linguistic values quantification and to consider an example of its application to the relationship types between users in the popular social network in Russia “VK”. To achieve this aim, we used the results of a sociological survey, by which were found the frequency of the order, then the probability theory apparatus was used. This research can be useful in studying of the influence of the types of users’ relationships on the execution of requests, also finds its use in building social graph of the organization’s employees and indirectly in obtaining estimates of the success of multi-pass Social engineering attacks propagation.


Social engineering Multi-pass social engineering attacks Linguistic variables Linguistic values Quantification Analysis of social graph of company employees Frequencies 


  1. 1.
    Abramov, M., Tulupyeva, T., Tulupyev, A.: Social Engineering Attacks: social networks and user security estimates. SUAI, St. Petersburg (2018), 266 p.Google Scholar
  2. 2.
    Azarov, A.A., Abramov, M.V., Tulupyeva, T.V., Tulupyev, A.L.: Users’ of Information System Protection Analysis from Malefactor’s Social Engineering Attacks Taking into Account Malefactor’s Competence Profile, Biologically Inspired Cognitive Architectures (BICA) for Young Scientists, pp. 25–30 (2016)Google Scholar
  3. 3.
    Bapna, R., Gupta, A., Rice, S., Sundararajan, A.: Trust and the strength of ties in online social networks: an exploratory field experiment. MIS Q. 41(1), 115–130 (2017)CrossRefGoogle Scholar
  4. 4.
    Curtis, S.R., Rajivan, P., Jones, D.N., Gonzalez, C.: Phishing attempts among the dark triad: patterns of attack and vulnerability. Comput. Hum. Behav. 87, 174–182 (2018)CrossRefGoogle Scholar
  5. 5.
  6. 6.
    Fifth Bronx Man Pleads Guilty In Multimillion-Dollar Ghana-Based Fraud Scheme Involving Business Email Compromises And Romance Scams Targeting Elderly. Accessed 15 Apr 2019
  7. 7.
    Is social engineering the biggest threat to your organization? Accessed 12 Dec 2018
  8. 8.
    Kharitonov, N.A., Maximov, A.G., Tulupyev, A.L.: Algebraic Bayesian networks: the use of parallel computing while maintaining various degrees of consistency. Studies in Systems, Decision and Control, vol. 199, pp. 696–704. Springer (2019)Google Scholar
  9. 9.
    Khlobystova, A.O., Abramov, M.V., Tulupyev, A.L., Zolotin, A.A.: Identifying the most critical trajectory of the spread of a social engineering attack between two users. Informatsionno-upravliaiushchie sistemy (Inf. Control Syst.) 6, 74–81 (2018)Google Scholar
  10. 10.
    Khovanov, N.V.: Measurement of a discrete indicator utilizing nonnumerical, inaccurate, and incomplete information. Meas. Tech. 46(9), 834–838 (2003)CrossRefGoogle Scholar
  11. 11.
    Leading active social media platforms in Russia in 2018. Accessed 10 Apr 2019
  12. 12.
    Maiz, A., Arranz, N., Fdez. de Arroyabe, J.C.: Factors affecting social interaction on social network sites: the Facebook case. J. Enterp. Inf. Manag. 29(5), 630–649 (2016)Google Scholar
  13. 13.
    Schifferle. L.W.: Romance scams will cost you. Accessed 04 Apr 2019
  14. 14.
    Suleimanov, A., Abramov, M., Tulupyev, A.: Modelling of the social engineering attacks based on social graph of employees communications analysis. In: Proceedings of 2018 IEEE Industrial Cyber-Physical Systems (ICPS), St.-Petersburg, pp. 801–805 (2018)Google Scholar
  15. 15.
    Tulupyev, A., Kharitonov, N., Zolotin, A.: Algebraic Bayesian networks: consistent fusion of partially intersected knowledge systems. In: The Second International Scientific and Practical Conference “Fuzzy Technologies in the Industry – FTI 2018”. CEUR Workshop Proceedings, pp. 109–115 (2018)Google Scholar
  16. 16.
    Weekly Threat Report 10th August 2018. Accessed 19 Feb 2019
  17. 17.
    Yang, Z., Kong, X., Sun, J., Zhang, Y.: Switching to green lifestyles: behavior change of ant forest users. Int. J. Environ. Res. Public Health 15(9), 1819 (2018)CrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Laboratory of Theoretical and Interdisciplinary Problems of InformaticsSt. Petersburg Institute for Informatics and Automation of the Russian Academy of SciencesSt. PetersburgRussia
  2. 2.Mathematics and Mechanics FacultySt. Petersburg State UniversitySt. PetersburgRussia

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