Skip to main content
SpringerLink
Log in

Information Security Incident Forecasting

  • Published:
Automatic Control and Computer Sciences Aims and scope Submit manuscript

Abstract

This article suggests methodological approaches to building conventionally determined and stochastic models of forecasting damages from security incidents in information systems of different applications. The original information for modeling includes a priori data on the possible kind of forecast processes; these data are derived from experience in running similar information systems and from expert estimates. The information for modeling also includes statistics on temporary and volumetric characteristics of damage from security incidents in the examined system. The data fusion is based on the maximum uncertainty principle.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

REFERENCES

  1. Anisimov, V.G., Anisimov, E.G., Zegzhda, P.D., Saurenko, T.N., and Prisyazhnyuk, S.P., Indices of the effectiveness of information protection in an information interaction system for controlling complex distributed organizational objects, Autom. Control Comput. Sci., 2017, vol. 51, no. 8, pp. 824–828.  https://doi.org/10.3103/S0146411617080053

    Article  Google Scholar 

  2. Anisimov, V.G., Zegzhda, D.P., Anisimov, E.G., and Bazhin, D.A., A risk-oriented approach to the control arrangement of security protection subsystems of information systems Autom. Control Comput. Sci., 2016, vol. 50, no. 8, pp. 717–721.  https://doi.org/10.3103/S0146411616080289

    Article  Google Scholar 

  3. Zegzhda, D.P. and Pavlenko, E.Yu., Cyber-sustainability of software-defined networks based on situational management, Autom. Control Comput. Sci., 2018, vol. 52, no. 8, pp. 984–992.  https://doi.org/10.3103/S0146411618080291

    Article  Google Scholar 

  4. Zegzhda, D., Lavrova, D., and Poltavtseva, M., Multifractal security analysis of cyberphysical systems, Nonlinear Phenom. Complex Syst. (Minsk, Belarus), 2019, vol. 22, no. 2, pp. 196–204.

    Google Scholar 

  5. Pavlenko, E.Yu., Yarmak, A.V., and Moskvin, D.A., Hierarchical approach to analyzing security breaches in information systems, Autom. Control Comput. Sci., 2017, vol. 51, no. 8, pp. 829–834.  https://doi.org/10.3103/S0146411617080144

    Article  Google Scholar 

  6. Anisimov, V.G., Anisimov, E.G., Saurenko, T.N., and Sonkin, M.A., The model and the planning method of volume and variety assessment of innovative products in an industrial enterprise, J. Phys.: Conf. Ser., 2017, vol. 803, p. 012006.  https://doi.org/10.1088/1742-6596/803/1/012006

    Article  Google Scholar 

  7. Saurenko, T., Anisimov, E., Anisimov, V., and Levina, A., Comparing investment projects of innovative developing strategies of municipalities, based on a set of indicators, MATEC Web Conf., 2018, vol. 170, p. 01038.  https://doi.org/10.1051/matecconf/201817001038

  8. Anisimov, V., Chernysh, A., and Anisimov, E., Model and algorithm for substantiating solutions for organization of high-rise construction project, E3S Web Conf., 2018, vol. 33, p. 03003.  https://doi.org/10.1051/e3sconf/20183303003

  9. Jaynes, E.T., Information theory and statistical mechanics, Phys. Rev., 1957, vol. 106, pp. 620–630.  https://doi.org/10.1103/PhysRev.106.620

    Article  MathSciNet  MATH  Google Scholar 

  10. Alekseyev, A.O., Alekseyev, O.G., Anisimov, V.G., Anisimov, E.G., and Yachkula, N.I., Application of Markov chains in estimating the computational complexity of the simplex method, Sov. J. Comput. Syst. Sci., 1988, vol. 5, pp. 130–134.

    MathSciNet  MATH  Google Scholar 

  11. Anisimov, V.G., Anisimov, E.G., and Gertsev, V.N., Assessing efficiency of the system of missile and artillery armament of missile forces and artillery, Mil. Thought, 2001, vol. 10, no. 4, pp. 45–54.

    Google Scholar 

  12. Anisimov, V.G. and Anisimov, E.G., Modification of the method for solving a class of integer programming problems, Comp. Math. Math. Phys., 1997, vol. 37, no. 2, pp. 179–183.

    MathSciNet  MATH  Google Scholar 

  13. Anisimov, E.G., Anisimov, V.G., and Sonkin, M.A., Mathematical simulation of adaptive allocation of discrete resources, Proc. 2016 Conf. on Information Technologies in Science, Management, Social Sphere and Medicine, 2016, Atlantis Press, 2016, pp. 280–283.  https://doi.org/10.2991/itsmssm-16.2016.57

  14. Anisimov, V., Anisimov, E., and Sonkin, M., A resource-and-time method to optimize the performance of several interrelated operations, Int. J. Appl. Eng. Res., 2015, vol. 10, no. 17, pp. 38127–38132.

    Google Scholar 

  15. Anisimov, V.G. and Anisimov, E.G., A branch-and-bound algorithm for one class of scheduling problem, Comput. Math. Math. Phys., 1992, vol. 32, no. 12, pp. 1827–1832.

    MathSciNet  MATH  Google Scholar 

  16. Anisimov, V.G. and Anisimov, E.G., A method of solving one class of integer programming problems, USSR Comp. Math. Math. Phys., 1989, vol. 29, no. 5, pp. 238–241.  https://doi.org/10.1016/0041-5553(89)90205-X

    Article  MATH  Google Scholar 

  17. Fishburn, P.C., Nonlinear Preference and Utility Theory, Baltimore: Johns Hopkins Univ. Press, 1988.

    MATH  Google Scholar 

  18. Gumbel, E.J., Statistical Theory of Extreme Values and Some Practical Applications: A Series of Lectures. U.S. Department of Commerce, National Bureau of Standards, 1954, vol. 33.

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Peter the Great St. Petersburg Polytechnic University, 195251, St. Petersburg, Russia

    V. G. Anisimov

  2. Peoples’ Friendship University of Russia, 117198, Moscow, Russia

    T. N. Saurenko & E. G. Anisimov

  3. St. Petersburg Federal Research Center, Russian Academy of Sciences, 199178, St. Petersburg, Russia

    V. V. Kasatkin

  4. MIREA—Russian Technological University, 119454, Moscow, Russia

    V. P. Los’

Authors
  1. T. N. Saurenko
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. V. G. Anisimov
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. E. G. Anisimov
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. V. V. Kasatkin
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. V. P. Los’
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to V. G. Anisimov or V. P. Los’.

Ethics declarations

The authors declare that they have no conflicts of interest.

Additional information

Translated by S. Kuznetsov

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Saurenko, T.N., Anisimov, V.G., Anisimov, E.G. et al. Information Security Incident Forecasting. Aut. Control Comp. Sci. 55, 903–907 (2021). https://doi.org/10.3103/S0146411621080277

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S0146411621080277

Keywords:

Search

Navigation