| Datum
|
2021/11/03 12:00 – 2021/11/03 13:00
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| Ort
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Gebäude 50.34, Raum 348 + MS Teams (hybrid)
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| Vortragende(r)
|
Tobias Walter
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| Forschungsgruppe
|
AbQP
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| Titel
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P2CySeMoL: Predictive, Probabilistic Cyber Security Modeling Language
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| Autoren
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Hannes Holm, Khurram Shahzad, Markus Buschle, Mathias Ekstedt
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| PDF
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https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6990572
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| URL
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https://doi.org/10.1109/TDSC.2014.2382574
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| BibTeX
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https://dblp.org/rec/journals/tdsc/HolmSBE15.html?view=bibtex
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| Abstract
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This paper presents the Predictive, Probabilistic Cyber Security Modeling Language (P 2 CySeMoL), an attack graph tool that can be used to estimate the cyber security of enterprise architectures. P 2 CySeMoL includes theory on how attacks and defenses relate quantitatively; thus, users must only model their assets and how these are connected in order to enable calculations. The performance of P 2 CySeMoL enables quick calculations of large object models. It has been validated on both a component level and a system level using literature, domain experts, surveys, observations, experiments and case studies.
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