DOI

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.

Язык оригиналаанглийский
Название основной публикацииProceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021
РедакторыS. Shaposhnikov
ИздательInstitute of Electrical and Electronics Engineers Inc.
Страницы49-51
Число страниц3
ISBN (электронное издание)9781665439749
DOI
СостояниеОпубликовано - 26 мая 2021
Событие24th International Conference on Soft Computing and Measurements, SCM 2021 - St. Petersburg, Российская Федерация
Продолжительность: 26 мая 202128 мая 2021

конференция

конференция24th International Conference on Soft Computing and Measurements, SCM 2021
Страна/TерриторияРоссийская Федерация
ГородSt. Petersburg
Период26/05/2128/05/21

    Предметные области Scopus

  • Искусственный интеллект
  • Математика и теория расчета
  • Компьютерные сети и коммуникации
  • Прикладные компьютерные науки
  • Теория управления и исследование операций
  • Статистика, теория вероятности и теория неопределенности
  • Теория оптимизации
  • Моделирование и симуляция

ID: 87278331