A proof calculus for attack trees in Isabelle

Kammueller, Florian ORCID logoORCID: https://orcid.org/0000-0001-5839-5488 (2017) A proof calculus for attack trees in Isabelle. Data Privacy Management, Cryptocurrencies and Blockchain Technology: ESORICS 2017 International Workshops, DPM 2017 and CBT 2017, Oslo, Norway, September 14-15, 2017, Proceedings. In: 12th International Workshop on Data Privacy Management (DPM 2017), 14-15 Sept 2017, Oslo, Norway. ISBN 9783319678153. ISSN 0302-9743 [Conference or Workshop Item] (doi:10.1007/978-3-319-67816-0_1)

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Abstract

Attack trees are an important modeling formalism to identify and quantify attacks on security and privacy. They are very useful as a tool to understand step by step the ways through a system graph that lead to the violation of security policies. In this paper, we present how attacks can be refined based on the violation of a policy. To that end we provide a formal definition of attack trees in Isabelle’s Higher Order Logic: a proof calculus that defines how to refine sequences of attack steps into a valid attack. We use a notion of Kripke semantics as formal foundation that then allows to express attack goals using branching time temporal logic CTL. We illustrate the use of the mechanized Isabelle framework on the example of a privacy attack to an IoT healthcare system.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Paper published as:
Kammüller F. (2017) A Proof Calculus for Attack Trees in Isabelle. In: Garcia-Alfaro J., Navarro-Arribas G., Hartenstein H., Herrera-Joancomartí J. (eds) Data Privacy Management, Cryptocurrencies and Blockchain Technology. DPM 2017, CBT 2017. Lecture Notes in Computer Science, vol 10436. Springer, Cham
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 22344
Notes on copyright: The final publication is available at Springer via via http://dx.doi.org/10.1007/978-3-319-67816-0
Useful Links:
Depositing User: Florian Kammueller
Date Deposited: 10 Aug 2017 15:01
Last Modified: 08 Jun 2022 15:56
URI: https://eprints.mdx.ac.uk/id/eprint/22344

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