Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › Рецензирование
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. ред. / S. Shaposhnikov. Institute of Electrical and Electronics Engineers Inc., 2021. стр. 49-51 9507195.Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › Рецензирование
}
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