Soft Estimates for Social Engineering Attack Propagation Probabilities Depending on Interaction Rates Among Instagram Users

Abstract

The purpose of this article is to propose an approach to denoting the parameters of the model for assessing the probability of success of a multi-pass social engineering attack of an attacker on a user. These parameters characterize the evaluation of the probability of propagation of social engineering attacks from user to user in one type of interaction. These estimates are related to the intensity of user interaction, information about which is extracted from data obtained from social Media. The article proposes an approach to the conversion of information about the episodes of interaction between users in the social Media Instagram in assessing the probability of the spread of social engineering attack, based on the Khovanov method. The obtained results help produce social network analysis and serve as a basis for the subsequent analysis of possible trajectories of the spread of multi-pass social engineering attacks, allowing the simulation of social engineering attacks and automated calculation of estimates of the success of the attack on different trajectories. The novelty of the research is to the application quantification method to social links in the context of social engineering attacks.