Quantitative criteria for recognizing the incorrect behavior of computer network users

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Abstract

Two approaches for recognizing the incorrect behavior of computer network users are presented. The first one relies on the technique of statistical hypotheses testing and uses self-organizing feature maps (Kohonen networks) for generating target statistics. The second approach recognizes dangerous activity using executed sequences of relevant typical actions, with their dynamics being represented with the aid of Markov chains.

General Information

Keywords: computer network threats, user activity, self-organizing feature maps, Markov chains

Journal rubric: Mathematical Psychology

Article type: scientific article

DOI: https://doi.org/10.17759/exppsy.2018110302

For citation: Kuravsky L.S., Yuryev G.A., Scribtsov P.V., Chervonenkis M.A., Konstantinovsky A.A., Shevchenko A.A., Isakov S.S. Quantitative criteria for recognizing the incorrect behavior of computer network users. Eksperimental'naâ psihologiâ = Experimental Psychology (Russia), 2018. Vol. 11, no. 3, pp. 19–35. DOI: 10.17759/exppsy.2018110302. (In Russ., аbstr. in Engl.)

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Information About the Authors

Lev S. Kuravsky, Doctor of Engineering, professor, Dean of the Computer Science Faculty, Moscow State University of Psychology and Education, Moscow, Russia, ORCID: https://orcid.org/0000-0002-3375-8446, e-mail: l.s.kuravsky@gmail.com

Grigory A. Yuryev, PhD in Physics and Matematics, Associate Professor, Head of Department of the Computer Science Faculty, Leading Researcher, Youth Laboratory Information Technologies for Psychological Diagnostics, Moscow State University of Psychology and Education, Moscow, Russia, ORCID: https://orcid.org/0000-0002-2960-6562, e-mail: g.a.yuryev@gmail.com

P. V. Scribtsov, PhD in Engineering, General Director, Pavlin Techno, Moscow, Russia, e-mail: pvs@pawlin.ru

M. A. Chervonenkis, Leading Researcher, Pavlin Techno, Moscow, Russia, e-mail: chervonenkis@yandex.ru

A. A. Konstantinovsky, Student, Faculty of Information Technology, Moscow State University of Psychology & Education, Moscow, Russia, e-mail: sanekkonst@gmail.com

A. A. Shevchenko, Master Student, Faculty of Information Technology, Moscow State University of Psychology & Education, Moscow, Russia, e-mail: apokend@gmail.com

Sergey S. Isakov, Lecturer, Postgraduate Student of the Computer Science Faculty, Moscow State University of Psychology & Education, Moscow, Russia, ORCID: https://orcid.org/0000-0003-1719-2355, e-mail: isakovss@mgppu.ru

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