Quantitative criteria for recognizing the incorrect behavior of computer network users-Reference-Cited by-同舟云学术

Quantitative criteria for recognizing the incorrect behavior of computer network users

Published:2018 Issue:3 Volume:11 Page:19-35
ISSN:2072-7593
Container-title:Experimental Psychology (Russia)
language:
Short-container-title:

Author:

Kuravsky L.S.¹,Yuryev G.A.²^ORCID,Scribtsov P.V.³,Chervonenkis M.A.³,Konstantinovsky A.A.²,Shevchenko A.A.²,Isakov S.S.²

Affiliation:

1. Moscow State University of Psychology and Education

2. Moscow State University of Psychology & Education

3. Pavlin Techno

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.

Publisher

Federal State-Financed Educational Institution of Higher Education Moscow State University of Psychology and Education

Link

https://psyjournals.ru/files/95563/exppsy_2018_n3_Kuravsky_Yuryevet_et_al.pdf

Reference27 articles.

1. Bolâshev A.K. Algoritmy preobrazovaniya i klassifikacii trafika dlya obnaruzheniya vtorzhenij v kompâyuternye seti: diss. ... kand. tekhn. Nauk [Algorithms of classification of traffic for inclusion in computer networks. PhD thesis]. 05.13.11, 05.13.19 SPb, Gos. ehlektrotekhn. un-t (LEHTI), 2011, 155 p. (In Russ.).

2. Dajneko V.YU. Razrabotka modeli i algoritmov obnaruzheniya vtorzhenij na osnove dinamicheskih bajesovskih setej: diss. ... kand. tekhn. Nauk [Development of a model and algorithms of detection of inclusions based on dynamic Bayesian networks. PhD thesis]. SPb, Nac. issled. un-t informac. tekhnologij, mekhaniki i optiki, 2013, 131 p. (In Russ.).

3. Kuravskiy L.S., Margolis A.A., Marmalyuk P.A., Panfilova A.S., YUrâev G.A. Matematicheskie aspekty koncepcii adaptivnogo trenazhera [Mathematical aspects of the conception of an adaptive training]. Psihologicheskaya nauka i obrazovanie [Psychological science and education], 2016, vol. 21, no. 2, pp. 84â95. doi: 10.17759/pse.2016210210. (In Russ.).

4. Kuravskiy L.S., Yuriev G.A. Veroyatnostnyj metod filâtraciiartefaktov pri adaptivnom testirovanii [Probability method of filtration in adaptive testing]. Eksperimentalânaya psihologiya [Experimental Psychology], 2012, vol. 5. no. 1, pp. 119â131. (In Russ.).

5. Kuravskiy L.S., Yuriev G.A. Ispolâzovanie markovskih modelej pri obrabotke rezulâtatov testirovaniya [Using Markov models for testing analysis]. Voprosy psihologii [Issues in Psychology], 2011, no. 2, pp. 98â 107.