Ruijters, E.J.J. and Schivo, S. and Stoelinga, M.I.A. and Rensink, A.
Uniform analysis of fault trees through model transformations.
In: Proceedings of the 63rd Annual Reliabliity and Maintainability Symposium (RAMS 2017), 23-26 Jan 2017, Orlando, FL, USA.
IEEE Reliability Society.
Full text available as:
Official URL: http://dx.doi.org/10.1109/RAM.2017.7889759
As the critical systems we rely on every day, such as nuclear power plants and airplanes, become ever more complex, the need to rigorously verify the safety and dependability of these systems is becoming very clear. Furthermore, deliberate attacks have become a prominent cause of concern for safety and reliability.
One of the most prominent techniques for analyzing such systems is fault tree analysis (FTA), and a whole forest of variants, extensions, and analysis tools have been developed. In the security field, FTA was the inspiration for attack trees, used to analyze systems for vulnerability to malicious attacks. These formalisms are rarely compatible, making it difficult to exploit their different strengths in analyzing the same system.
The key contribution of this paper is a meta-model describing many varieties of fault and attack trees, and well as combined attack-fault trees. We provide translations to and from different formalisms, as well as our own analysis engine for combined models. We demonstrate this framework on three case studies.
|Item Type:||Conference or Workshop Paper (Full Paper, Talk)|
|Research Group:||EWI-FMT: Formal Methods and Tools|
|Research Project:||ArRangeer: smARt Railroad maintenance eNGinEERing with stochastic model checking, TREsPASS: Technology-supported Risk Estimation By Predictive Assessment Of Socio-technical Security|
|Additional Information:||Foreground = 25%; Type of activity = conference; Main leader = UT; Type of audience = scientific community; Size of audience = 40; Countries addressed = international;|
|Uncontrolled Keywords:||Attack-fault trees, Fault tree analysis, meta-modelling|
|Deposited On:||01 November 2016|
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