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@inproceedings{1783877, author = {Macák, Martin and Bojnák, Štefan and Bühnová, Barbora}, address = {New York}, booktitle = {Proceedings of the 16th Conference on Computer Science and Intelligence Systems}, doi = {http://dx.doi.org/10.15439/2021F85}, keywords = {insider attack; process mining; security; unintentional perpetrator; attack vector; case study}, howpublished = {elektronická verze "online"}, language = {eng}, location = {New York}, isbn = {978-83-959183-8-4}, pages = {349-356}, publisher = {IEEE}, title = {Identification of Unintentional Perpetrator Attack Vectors using Simulation Game: A Case Study}, url = {https://ieeexplore.ieee.org/abstract/document/9555700}, year = {2021} }
TY - JOUR ID - 1783877 AU - Macák, Martin - Bojnák, Štefan - Bühnová, Barbora PY - 2021 TI - Identification of Unintentional Perpetrator Attack Vectors using Simulation Game: A Case Study PB - IEEE CY - New York SN - 9788395918384 KW - insider attack KW - process mining KW - security KW - unintentional perpetrator KW - attack vector KW - case study UR - https://ieeexplore.ieee.org/abstract/document/9555700 N2 - In our digital era, insider attacks are among the serious underresearched areas of the cybersecurity landscape. A significant type of insider attack is facilitated by employees without malicious intent. They are called unintentional perpetrators. We proposed mitigating these threats using a simulation-game platform to detect the potential attack vectors. This paper introduces and implements a scenario that demonstrates the usability of this approach in a case study. This work also helps to understand players' behavior when they are not told upfront that they will be a target of social engineering attacks. Furthermore, we provide relevant acquired observations for future research. ER -
MACÁK, Martin, Štefan BOJNÁK a Barbora BÜHNOVÁ. Identification of Unintentional Perpetrator Attack Vectors using Simulation Game: A Case Study. Online. In \textit{Proceedings of the 16th Conference on Computer Science and Intelligence Systems}. New York: IEEE, 2021, s.~349-356. ISBN~978-83-959183-8-4. Dostupné z: https://dx.doi.org/10.15439/2021F85.
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