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

• Published in: 2021 XXIV International Conference on Soft Computing and Measurements (SCM) pp. 49 - 51
• Main Authors: Khlobystova, Anastasiia O., Abramov, Maxim V.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 26.05.2021
• Subjects: Adaptation models; Analytical models; Bayes methods; Computational modeling; intensity of users interaction; Mathematical model; model of informational influence; Organizations; Security; social engineering attacks; social graphs
• DOI: 10.1109/SCM52931.2021.9507195

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.