Other formats:
BibTeX
LaTeX
RIS
@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 and 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, p.~349-356. ISBN~978-83-959183-8-4. Available from: https://dx.doi.org/10.15439/2021F85.
|
