Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
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.
Original language | English |
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Title of host publication | Proceedings of the 2nd International Scientific Conference on Intelligent Information Technologies for Industry, IITI 2017 |
Editors | Sergey Kovalev, Andrey Sukhanov, Margreta Vasileva, Valery Tarassov, Vaclav Snasel, Ajith Abraham |
Publisher | Springer Nature |
Pages | 441-447 |
Number of pages | 7 |
ISBN (Print) | 9783319683201 |
DOIs | |
State | Published - 1 Jan 2018 |
Event | 2nd International Conference on Intelligent Information Technologies for Industry, IITI 2017 - Varna, Bulgaria Duration: 14 Sep 2017 → 16 Sep 2017 |
Name | Advances in Intelligent Systems and Computing |
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Volume | 679 |
ISSN (Print) | 2194-5357 |
Conference | 2nd International Conference on Intelligent Information Technologies for Industry, IITI 2017 |
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Country/Territory | Bulgaria |
City | Varna |
Period | 14/09/17 → 16/09/17 |
ID: 36751974