TY - GEN

T1 - Approaches to merging linguistic values - Users relationships

AU - Khlobystova, Anastasiia O.

AU - Tulupyev, Alexander L.

N1 - Publisher Copyright: © 2020 Copyright for this paper by its authors.

PY - 2020

Y1 - 2020

N2 - Social engineering attacks based on the human factor have long been the most frequently used in violation of the information security policies. One of the ways to increase the organization's level of protection against social engineering attacks is building a social graph of the organization's employees and its analysis. The nodes of such graph associated with users of the information system, and edge designate the relationships between them. Moreover, this kind of information can be obtained by analyzing social networks. However, often users have accounts in different social networks, and the information presented in them is different. The purpose of this article became to propose approaches to merging probabilistic estimates of the relationship between users, which are linguistic values of linguistic variable "type of relationship". The theoretical significance of the results lies in the proposal of new approaches to the merging of probabilistic estimates of linguistic variables, the practical significance consist in creating the basis for further analysis of the social graph of the organization's employees, in particular, for detecting the most critical trajectories of attack development or solving backtracking tasks of social engineering attacks, e.i. the investigation of cyber crime committed by using social engineering techniques.

AB - Social engineering attacks based on the human factor have long been the most frequently used in violation of the information security policies. One of the ways to increase the organization's level of protection against social engineering attacks is building a social graph of the organization's employees and its analysis. The nodes of such graph associated with users of the information system, and edge designate the relationships between them. Moreover, this kind of information can be obtained by analyzing social networks. However, often users have accounts in different social networks, and the information presented in them is different. The purpose of this article became to propose approaches to merging probabilistic estimates of the relationship between users, which are linguistic values of linguistic variable "type of relationship". The theoretical significance of the results lies in the proposal of new approaches to the merging of probabilistic estimates of linguistic variables, the practical significance consist in creating the basis for further analysis of the social graph of the organization's employees, in particular, for detecting the most critical trajectories of attack development or solving backtracking tasks of social engineering attacks, e.i. the investigation of cyber crime committed by using social engineering techniques.

KW - Interaction intensity estimates

KW - Linguistic variable values

KW - Merging social networks

KW - Social engineering attacks

KW - Soft computing

UR - http://www.scopus.com/inward/record.url?scp=85092265523&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:85092265523

VL - 2648

T3 - CEUR Workshop Proceedings

SP - 210

EP - 218

BT - Conference on Artificial Intelligence 2020. CEUR Workshop Proceedings

T2 - 2020 "Russian Advances in Artificial Intelligence", RAAI 2020

Y2 - 10 October 2020 through 16 October 2020

ER -