Case Studies of Network Defense with Attack Graph Games
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F16%3A00307370" target="_blank" >RIV/68407700:21230/16:00307370 - isvavai.cz</a>
Result on the web
<a href="http://ieeexplore.ieee.org/document/7579429/" target="_blank" >http://ieeexplore.ieee.org/document/7579429/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/MIS.2016.74" target="_blank" >10.1109/MIS.2016.74</a>
Alternative languages
Result language
angličtina
Original language name
Case Studies of Network Defense with Attack Graph Games
Original language description
The increaing complexity of securing modern computer networks makes decision support systems an important tool for administrators. A challenge many existing tools fail to address is that attackers react strategically to new security measures, adapting their behaviors in response. Game theory provides a methodology for making decisions that takes into account these reactions, rather than assuming static attackers. The authors present an overview of how game theory can be used to inform one type of security decision: how to optimally place honeypots in a network. They demonstrate this approach on a realistic case study and present initial validation results based on a study comparing their approach with human decision makers.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GA15-23235S" target="_blank" >GA15-23235S: Abstractions and Extensive-Form Games with Imperfect Recall</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Intelligent Systems
ISSN
1541-1672
e-ISSN
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Volume of the periodical
31
Issue of the periodical within the volume
5
Country of publishing house
US - UNITED STATES
Number of pages
7
Pages from-to
24-30
UT code for WoS article
000385623600004
EID of the result in the Scopus database
2-s2.0-84992751039