Isabelle Modelchecking for insider threats

Kammueller, Florian ORCID logoORCID: (2016) Isabelle Modelchecking for insider threats. Data Privacy Management and Security Assurance: 11th International Workshop, DPM 2016 and 5th International Workshop, QASA 2016, Heraklion, Crete, Greece, September 26-27, 2016, Proceedings. In: 11th DPM International Workshop on Data Privacy Management (DPM 2016) co-located with ESORICS 2016, 26-27 Sept 2016, Heraklion, Crete, Greece. ISBN 9783319470719. ISSN 0302-9743 [Conference or Workshop Item] (doi:10.1007/978-3-319-47072-6_13)

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The Isabelle Insider framework formalises the technique of social explanation for modeling and analysing Insider threats in infrastructures including physical and logical aspects. However, the abstract Isabelle models need some refinement to provide sufficient detail to explore attacks constructively and understand how the attacker proceeds. The introduction of mutable states into the model leads us to use the concepts of Modelchecking within Isabelle. Isabelle can simply accommodate classical CTL type Modelchecking. We integrate CTL Modelchecking into the Isabelle Insider framework. A running example of an IoT attack on privacy motivates the method throughout and illustrates how the enhanced framework fully supports realistic modeling and analysis of IoT Insiders.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Paper published as chapter in: Data Privacy Management and Security Assurance, 2016, Volume 9963 of the series Lecture Notes in Computer Science pp 196-210
Research Areas: A. > School of Science and Technology > Computer Science > Foundations of Computing group
Item ID: 20407
Notes on copyright: Attached is an author accepted manuscript version of a paper published in Lecture Notes in Computer Science; made available in this repository in accordance with the publisher's self-archiving policy. The final publication is available at Springer via
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Depositing User: Florian Kammueller
Date Deposited: 02 Sep 2016 12:01
Last Modified: 08 Jun 2022 06:25

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