Formal modeling and analysis with humans in infrastructures for IoT health care systems

Kammueller, Florian (2017) Formal modeling and analysis with humans in infrastructures for IoT health care systems. In: 5th International Conference on Human Aspects of Security, Privacy and Trust, HCII-HAS 2017, 09-14 Jul 2017, Vancouver, BC, Canada. (doi:10.1007/978-3-319-58460-7_24)

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Abstract

In this paper, we integrate previously developed formal methods to model infrastructure, actors, and policies of human centric infrastructures in order to analyze security and privacy properties. A fruitful approach for discovering attacks on human centric infrastructure models is invalidation of global policies. Invalidating global policies by a complete exploration of the state space can be realized by modelchecking. To counter the state explosion problem inherent in modelchecking, Higher Order Logic (HOL) supported by the interactive theorem prover Isabelle can be used to emulate modelchecking. In addition, the Isabelle Insider framework supports modeling and analysis of human centric infrastructures including attack trees. In this paper, we investigate how Isabelle modelchecking might help to improve detection of attack traces and re-finement of attack tree analysis. To this end, we use a case study from security and privacy of IoT devices in the health care sector as proposed in the CHIST-ERA project SUCCESS.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Paper published as: Kammüller F. (2017) Formal Modeling and Analysis with Humans in Infrastructures for IoT Health Care Systems. In: Tryfonas T. (eds) Human Aspects of Information Security, Privacy and Trust. HAS 2017. Lecture Notes in Computer Science, vol 10292. Springer, Cham
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 21976
Notes on copyright: The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-58460-7_24
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Depositing User: Florian Kammueller
Date Deposited: 13 Jun 2017 09:43
Last Modified: 03 Apr 2019 06:42
ISBN: 9783319584591
URI: https://eprints.mdx.ac.uk/id/eprint/21976

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