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Adaptation of the Multi-pass social Engineering Attack Model Taking into Account Informational Influence. / Khlobystova, Anastasiia O.; Abramov, Maxim V.

Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021. ed. / S. Shaposhnikov. Institute of Electrical and Electronics Engineers Inc., 2021. p. 49-51 9507195.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Harvard

Khlobystova, AO & Abramov, MV 2021, Adaptation of the Multi-pass social Engineering Attack Model Taking into Account Informational Influence. in S Shaposhnikov (ed.), Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021., 9507195, Institute of Electrical and Electronics Engineers Inc., pp. 49-51, 24th International Conference on Soft Computing and Measurements, SCM 2021, St. Petersburg, Russian Federation, 26/05/21. https://doi.org/10.1109/scm52931.2021.9507195

APA

Khlobystova, A. O., & Abramov, M. V. (2021). Adaptation of the Multi-pass social Engineering Attack Model Taking into Account Informational Influence. In S. Shaposhnikov (Ed.), Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021 (pp. 49-51). [9507195] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/scm52931.2021.9507195

Vancouver

Khlobystova AO, Abramov MV. Adaptation of the Multi-pass social Engineering Attack Model Taking into Account Informational Influence. In Shaposhnikov S, editor, Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 49-51. 9507195 https://doi.org/10.1109/scm52931.2021.9507195

Author

Khlobystova, Anastasiia O. ; Abramov, Maxim V. / Adaptation of the Multi-pass social Engineering Attack Model Taking into Account Informational Influence. Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021. editor / S. Shaposhnikov. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 49-51

BibTeX

@inproceedings{e169bccadb474ac88df6f50ab71aacd1,
title = "Adaptation of the Multi-pass social Engineering Attack Model Taking into Account Informational Influence",
abstract = "One of the measures to prevent multi-pass social engineering attacks is to identify the chains of user, which are most susceptible to such attacks. The aim of the study is to combine a mathematical model for estimating the probability of success of the propagation of a multi-pass social engineering attack between users with a model for calculating information influence. Namely, it is proposed to include in estimating the intensity of interactions between users (which used in the model of the propagation of a multi-pass social engineering attack) estimating of power of influence actions of agents. The scientific significance of the work consists in the development of a mathematical structure for modeling the actions of an attacker-social engineer and creating a foundation for the subsequent analysis of the social graph of the organization's employees. The practical significance lies in the formation of opportunities for decision-makers. Therefore, they will be able to take more precise measures for increase the level of security as individual employees as the organization generally. ",
keywords = "intensity of users interaction, model of informational influence, social engineering attacks, social graphs",
author = "Khlobystova, {Anastasiia O.} and Abramov, {Maxim V.}",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 24th International Conference on Soft Computing and Measurements, SCM 2021 ; Conference date: 26-05-2021 Through 28-05-2021",
year = "2021",
month = may,
day = "26",
doi = "10.1109/scm52931.2021.9507195",
language = "English",
pages = "49--51",
editor = "S. Shaposhnikov",
booktitle = "Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",

}

RIS

TY - GEN

T1 - Adaptation of the Multi-pass social Engineering Attack Model Taking into Account Informational Influence

AU - Khlobystova, Anastasiia O.

AU - Abramov, Maxim V.

N1 - Publisher Copyright: © 2021 IEEE.

PY - 2021/5/26

Y1 - 2021/5/26

N2 - One of the measures to prevent multi-pass social engineering attacks is to identify the chains of user, which are most susceptible to such attacks. The aim of the study is to combine a mathematical model for estimating the probability of success of the propagation of a multi-pass social engineering attack between users with a model for calculating information influence. Namely, it is proposed to include in estimating the intensity of interactions between users (which used in the model of the propagation of a multi-pass social engineering attack) estimating of power of influence actions of agents. The scientific significance of the work consists in the development of a mathematical structure for modeling the actions of an attacker-social engineer and creating a foundation for the subsequent analysis of the social graph of the organization's employees. The practical significance lies in the formation of opportunities for decision-makers. Therefore, they will be able to take more precise measures for increase the level of security as individual employees as the organization generally.

AB - One of the measures to prevent multi-pass social engineering attacks is to identify the chains of user, which are most susceptible to such attacks. The aim of the study is to combine a mathematical model for estimating the probability of success of the propagation of a multi-pass social engineering attack between users with a model for calculating information influence. Namely, it is proposed to include in estimating the intensity of interactions between users (which used in the model of the propagation of a multi-pass social engineering attack) estimating of power of influence actions of agents. The scientific significance of the work consists in the development of a mathematical structure for modeling the actions of an attacker-social engineer and creating a foundation for the subsequent analysis of the social graph of the organization's employees. The practical significance lies in the formation of opportunities for decision-makers. Therefore, they will be able to take more precise measures for increase the level of security as individual employees as the organization generally.

KW - intensity of users interaction

KW - model of informational influence

KW - social engineering attacks

KW - social graphs

UR - http://www.scopus.com/inward/record.url?scp=85114032380&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/6e872189-7ed7-3392-98aa-1bfcfcf0d38f/

U2 - 10.1109/scm52931.2021.9507195

DO - 10.1109/scm52931.2021.9507195

M3 - Conference contribution

AN - SCOPUS:85114032380

SP - 49

EP - 51

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

A2 - Shaposhnikov, S.

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 24th International Conference on Soft Computing and Measurements, SCM 2021

Y2 - 26 May 2021 through 28 May 2021

ER -

ID: 87278331