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https://doi.org/10.1109/icit46...
Article . 2021 . Peer-reviewed
License: IEEE Copyright
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Prototyping intrusion detection in an industrial cloud-native digital twin

Authors: William Tärneberg; Per Skarin; Christian Gehrmann; Maria Kihl;

Prototyping intrusion detection in an industrial cloud-native digital twin

Abstract

Digital twins are poised to play a vital role in the industry 4.0 era. A cloud-based digital twin can augment the entity that it represents. To that effect, we envision that digital twins can have embedded control systems when paired with a cyber physical system, yielding significant performance and configurability advantages. However, relegating controllers to a cloud-based digital twin exposes them to a new set of attack surfaces. Given the intricacy of such systems and the plethora of mitigating actions they can take, intrusion detection is integral to maintaining the integrity of such system. In this paper, we propose and prototype a cloud-native digital twin proof of concept for evaluating the viability of the concept. The resulting platform is evaluated for its ability to host a cyber-physical system and its potential to incorporate an intrusion detection system.

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Sweden
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Keywords

Communication Systems

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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Top 10%
Green