Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
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 оригинала | английский |
|---|---|
| Название основной публикации | Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021 |
| Редакторы | S. Shaposhnikov |
| Издатель | Institute of Electrical and Electronics Engineers Inc. |
| Страницы | 49-51 |
| Число страниц | 3 |
| ISBN (электронное издание) | 9781665439749 |
| DOI | |
| Состояние | Опубликовано - 26 мая 2021 |
| Событие | 24th International Conference on Soft Computing and Measurements, SCM 2021 - St. Petersburg, Российская Федерация Продолжительность: 26 мая 2021 → 28 мая 2021 |
| конференция | 24th International Conference on Soft Computing and Measurements, SCM 2021 |
|---|---|
| Страна/Tерритория | Российская Федерация |
| Город | St. Petersburg |
| Период | 26/05/21 → 28/05/21 |
ID: 87278331