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) (KAR id:67496)
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Official URL: 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) |
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DOI/Identification number: | 10.1007/978-3-319-39381-0_21 |
Subjects: |
Q Science T Technology |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing |
Depositing User: | Jason Nurse |
Date Deposited: | 03 Jul 2018 13:12 UTC |
Last Modified: | 05 Nov 2024 11:07 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/67496 (The current URI for this page, for reference purposes) |
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