Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
Approach to identifying of employees profiles in websites of social networks aimed to analyze social engineering vulnerabilities. / Shindarev, Nikita; Bagretsov, Georgiy; Abramov, Maksim; Tulupyeva, Tatiana; Suvorova, Alena.
Proceedings of the 2nd International Scientific Conference on Intelligent Information Technologies for Industry, IITI 2017. ред. / Sergey Kovalev; Andrey Sukhanov; Margreta Vasileva; Valery Tarassov; Vaclav Snasel; Ajith Abraham. Springer Nature, 2018. стр. 441-447 (Advances in Intelligent Systems and Computing; Том 679).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
}
TY - GEN
T1 - Approach to identifying of employees profiles in websites of social networks aimed to analyze social engineering vulnerabilities
AU - Shindarev, Nikita
AU - Bagretsov, Georgiy
AU - Abramov, Maksim
AU - Tulupyeva, Tatiana
AU - Suvorova, Alena
N1 - Shindarev N., Bagretsov G., Abramov M., Tulupyeva T., Suvorova A. Approach to identifying of employees profiles in websites of social networks aimed to analyze social engineering vulnerabilities //Advances in Intelligent Systems and Computing. 2018. Vol. 679. P.441–447. DOI: 10.1007/978-3-319-68321-8_45
PY - 2018/1/1
Y1 - 2018/1/1
N2 - In current times, malefactors chances to succeed in performing a social engineering attack on company usually depends on how much personal information about employees he owns. Thus, search and analysis of public information about company’s employees from social network websites with purpose of protection company from malicious actions is important issue. This article is devoted to methods of identifying user’s online footprint in website of social network VK.com. Prototype of the tool for identifying employees public pages using binary decision trees as classifier is presented. Approach to fully automated gathering of training dataset is described.
AB - In current times, malefactors chances to succeed in performing a social engineering attack on company usually depends on how much personal information about employees he owns. Thus, search and analysis of public information about company’s employees from social network websites with purpose of protection company from malicious actions is important issue. This article is devoted to methods of identifying user’s online footprint in website of social network VK.com. Prototype of the tool for identifying employees public pages using binary decision trees as classifier is presented. Approach to fully automated gathering of training dataset is described.
KW - Information security
KW - Social engineering attacks
KW - Social networks
KW - User protection
KW - User’s vulnerabilities profile
KW - Social engineering attacks
KW - User protection
KW - Information security
KW - User’s vulnerabilities profile
KW - Social networks
UR - http://www.scopus.com/inward/record.url?scp=85031414399&partnerID=8YFLogxK
UR - http://www.mendeley.com/research/approach-identifying-employees-profiles-websites-social-networks-aimed-analyze-social-engineering-vu
U2 - 10.1007/978-3-319-68321-8_45
DO - 10.1007/978-3-319-68321-8_45
M3 - Conference contribution
AN - SCOPUS:85031414399
SN - 9783319683201
T3 - Advances in Intelligent Systems and Computing
SP - 441
EP - 447
BT - Proceedings of the 2nd International Scientific Conference on Intelligent Information Technologies for Industry, IITI 2017
A2 - Kovalev, Sergey
A2 - Sukhanov, Andrey
A2 - Vasileva, Margreta
A2 - Tarassov, Valery
A2 - Snasel, Vaclav
A2 - Abraham, Ajith
PB - Springer Nature
T2 - 2nd International Conference on Intelligent Information Technologies for Industry, IITI 2017
Y2 - 14 September 2017 through 16 September 2017
ER -
ID: 36751974