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Assessing the Degree of the Social Media User's Openness Using an Expert Model Based on the Bayesian Network. / Frolova, Marina S. ; Korepanova, Anastasiia A. ; Abramov, Maxim V. .

Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021. ред. / S. Shaposhnikov. 2021. стр. 52-55 9507111 (Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021).

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование

Harvard

Frolova, MS, Korepanova, AA & Abramov, MV 2021, Assessing the Degree of the Social Media User's Openness Using an Expert Model Based on the Bayesian Network. в S Shaposhnikov (ред.), Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021., 9507111, Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021, стр. 52-55, XXIV Международная конференция по мягким вычислениям и измерениям (SCM-2021), 26/05/21. https://doi.org/10.1109/SCM52931.2021.9507111

APA

Frolova, M. S., Korepanova, A. A., & Abramov, M. V. (2021). Assessing the Degree of the Social Media User's Openness Using an Expert Model Based on the Bayesian Network. в S. Shaposhnikov (Ред.), Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021 (стр. 52-55). [9507111] (Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021). https://doi.org/10.1109/SCM52931.2021.9507111

Vancouver

Frolova MS, Korepanova AA, Abramov MV. Assessing the Degree of the Social Media User's Openness Using an Expert Model Based on the Bayesian Network. в Shaposhnikov S, Редактор, Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021. 2021. стр. 52-55. 9507111. (Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021). https://doi.org/10.1109/SCM52931.2021.9507111

Author

Frolova, Marina S. ; Korepanova, Anastasiia A. ; Abramov, Maxim V. . / Assessing the Degree of the Social Media User's Openness Using an Expert Model Based on the Bayesian Network. Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021. Редактор / S. Shaposhnikov. 2021. стр. 52-55 (Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021).

BibTeX

@inproceedings{35ca7b823a834fc7a621f591e7b9abe9,
title = "Assessing the Degree of the Social Media User's Openness Using an Expert Model Based on the Bayesian Network",
abstract = "One of the most topical problems of information security is the prevention of successful incidents of social engineering attacks - psychological manipulation of people to get access to confidential information. It is necessary to assess personal characteristics of an information system user to estimate his vulnerability to some type of attack. Assessment the degree of openness of a social media user is perspective this way (openness is considered according to the factor of 'openness to experience', which is part of the personality model 'The Big Five'). In this paper, we consider an approach to assessing the openness of an online social network user using the bayesian network. Based on the five-factor personality questionnaire, the characteristics that can be extracted from the user's page, potentially affecting his openness to accepting information, are considered. The structure of the Bayesian network for solving this problem is proposed.",
keywords = "Bayesian networks, social engineering attacks, social media",
author = "Frolova, {Marina S.} and Korepanova, {Anastasiia A.} and Abramov, {Maxim V.}",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; null ; Conference date: 26-05-2021 Through 28-05-2021",
year = "2021",
month = may,
day = "26",
doi = "10.1109/SCM52931.2021.9507111",
language = "English",
isbn = "978-1-6654-3975-6",
series = "Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021",
pages = "52--55",
editor = "S. Shaposhnikov",
booktitle = "Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021",

}

RIS

TY - GEN

T1 - Assessing the Degree of the Social Media User's Openness Using an Expert Model Based on the Bayesian Network

AU - Frolova, Marina S.

AU - Korepanova, Anastasiia A.

AU - Abramov, Maxim V.

N1 - Publisher Copyright: © 2021 IEEE.

PY - 2021/5/26

Y1 - 2021/5/26

N2 - One of the most topical problems of information security is the prevention of successful incidents of social engineering attacks - psychological manipulation of people to get access to confidential information. It is necessary to assess personal characteristics of an information system user to estimate his vulnerability to some type of attack. Assessment the degree of openness of a social media user is perspective this way (openness is considered according to the factor of 'openness to experience', which is part of the personality model 'The Big Five'). In this paper, we consider an approach to assessing the openness of an online social network user using the bayesian network. Based on the five-factor personality questionnaire, the characteristics that can be extracted from the user's page, potentially affecting his openness to accepting information, are considered. The structure of the Bayesian network for solving this problem is proposed.

AB - One of the most topical problems of information security is the prevention of successful incidents of social engineering attacks - psychological manipulation of people to get access to confidential information. It is necessary to assess personal characteristics of an information system user to estimate his vulnerability to some type of attack. Assessment the degree of openness of a social media user is perspective this way (openness is considered according to the factor of 'openness to experience', which is part of the personality model 'The Big Five'). In this paper, we consider an approach to assessing the openness of an online social network user using the bayesian network. Based on the five-factor personality questionnaire, the characteristics that can be extracted from the user's page, potentially affecting his openness to accepting information, are considered. The structure of the Bayesian network for solving this problem is proposed.

KW - Bayesian networks

KW - social engineering attacks

KW - social media

UR - http://www.scopus.com/inward/record.url?scp=85114016323&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/e7d563d5-97ce-38d7-822b-0030d9b59a72/

U2 - 10.1109/SCM52931.2021.9507111

DO - 10.1109/SCM52931.2021.9507111

M3 - Conference contribution

SN - 978-1-6654-3975-6

T3 - Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021

SP - 52

EP - 55

BT - Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021

A2 - Shaposhnikov, S.

Y2 - 26 May 2021 through 28 May 2021

ER -

ID: 85431561