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Attack Tree Analysis for Insider Threats on the IoT using Isabelle

Kammüller, Florian, Nurse, Jason R. C., Probst, Christian W. (2016) Attack Tree Analysis for Insider Threats on the IoT using Isabelle. In: Lecture Notes in Computer Science 9750. Lecture Notes in Computer Science . pp. 234-246. Springer, Switzerland ISBN 978-3-319-39380-3. (doi:10.1007/978-3-319-39381-0_21)

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http://dx.doi.org/10.1007/978-3-319-39381-0_21

Abstract

The Internet-of-Things (IoT) aims at integrating small devices around humans. The threat from human insiders in “regular” organisations is real; in a fully-connected world of the IoT, organisations face a substantially more severe security challenge due to unexpected access possibilities and information flow. In this paper, we seek to illustrate and classify insider threats in relation to the IoT (by ‘smart insiders’), exhibiting attack vectors for their characterisation. To model the attacks we apply a method of formal modelling of Insider Threats in the interactive theorem prover Isabelle. On the classified IoT attack examples, we show how this logical approach can be used to make the models more precise and to analyse the previously identified Insider IoT attacks using Isabelle attack trees.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1007/978-3-319-39381-0_21
Subjects: Q Science
T Technology
Divisions: Faculties > Sciences > School of Computing > Security Group
Depositing User: Jason Nurse
Date Deposited: 03 Jul 2018 13:12 UTC
Last Modified: 01 Aug 2019 10:43 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/67496 (The current URI for this page, for reference purposes)
Nurse, Jason R. C.: https://orcid.org/0000-0003-4118-1680
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