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On the adoption and deployment of secure and privacy-preserving IIoT in smart manufacturing: a comprehensive guide with recent advances

Authors: Abdullahi, Sani M.; Lazarova-Molnar, Sanja;

On the adoption and deployment of secure and privacy-preserving IIoT in smart manufacturing: a comprehensive guide with recent advances

Abstract

Abstract The adoption of the Internet of Things (IoT) in smart manufacturing has recently seen a boost in economic and technological advancement. This is attributed to improved operational efficiency resulting from streamlined interoperability, decreased downtime, and real-time processing as compared to conventional manufacturing industries. It also brings with it a massive deployment of intelligent systems and devices from both the Information Technology (IT) and Operational Technology (OT) realms within the Industrial IoT (IIoT) infrastructure, thus creating a heterogeneous interconnectivity. However, such inherent interconnectivity introduces significant security and privacy challenges. To mitigate these challenges, researchers and cybersecurity experts have recently proposed different defense mechanisms for the different facets of the cyber landscape within the IIoT infrastructure. Nevertheless, most of these techniques require major technical expertise to be implemented. Also, there is a lack of specific follow-through guides on how to adopt and implement such mechanisms. This paper aims to fill that gap by providing in-depth guidance on adopting and deploying different defense mechanisms designed to mitigate various cyber threats while ensuring secure and privacy-preserving IIoT infrastructure. The article first emphasizes the implications of cyber threats targeting IIoT tools and infrastructure as well as vulnerabilities emerging due to IT and OT convergence. It then delves into recent state-of-the-art protection mechanisms designed to mitigate these attacks based on a robust framework that includes all defenses. In addition, comprehensive guides to be adopted for a secure and privacy-preserving IIoT are provided. Finally, other challenges and open research questions are presented to pave the way towards efficient deployment of secure and privacy-preserving schemes for the IIoT in smart manufacturing.

Countries
Germany, Denmark
Keywords

info:eu-repo/classification/ddc/330, 330, ddc:330, Economics, Adoption, Deployment, Smart manufacturing, Industrial internet of things, 004, Security and privacy

  • BIP!
    Impact byBIP!
    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).
    28
    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.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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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!
28
Top 10%
Top 10%
Top 10%
Green
hybrid