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Cited by 357IoT and Edge/Fog ComputingDigital Transformation in IndustryInternet of Things and AI

The DOI matches its Crossref record; 148 of the 148 references it cites were found in a registry or an index.

A Survey on Digital Twins: Architecture, Enabling Technologies, Security and Privacy, and Future Prospects

Open access
Wang, Yuntao, Su, Zhou, Guo, Shaolong, Dai, Minghui, Luan, Tom H., Liu, Yiliang·2023·IEEE Internet of Things Journal
DOI 10.1109/jiot.2023.3263909

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Abstract

By interacting, synchronizing, and cooperating with its physical counterpart in real time, digital twin (DT) is promised to promote an intelligent, predictive, and optimized modern city. Via interconnecting massive physical entities and their virtual twins with inter-twin and intra-twin communications, the Internet of DTs (IoDT) enables free data exchange, dynamic mission cooperation, and efficient information aggregation for composite insights across vast physical/virtual entities. However, as IoDT incorporates various cutting-edge technologies to spawn the new ecology, severe known/unknown security flaws, and privacy invasions of IoDT hinder its wide deployment. Besides, the intrinsic characteristics of IoDT, such as decentralized structure, information-centric routing, and semantic communications, entail critical challenges for security service provisioning in IoDT. To this end, this article presents an in-depth review of the IoDT with respect to system architecture, enabling technologies, and security/privacy issues. Specifically, we first explore a novel distributed IoDT architecture with cyber–physical interactions and discuss its key characteristics and communication modes. Afterward, we investigate the taxonomy of security and privacy threats in IoDT, discuss the key research challenges, and review the state-of-the-art defense approaches. Finally, we point out the new trends and open research directions related to IoDT.

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Show all 139 references

Research works printed but not linked: 3

  1. 2022, Digital twin market-global forecast to 2027
  2. 10.5555/3241094.3241142 · DOI
  3. 2020, Digital Twin Framework For Manufacturing

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Metadata

Authors
Wang, Y., Su, Z., Guo, S., Dai, M., Luan, T. H., & Liu, Y.
Affiliations
  • Xi'an Jiaotong University (CN)
  • University of Macau (MO)
ORCID
Venue
IEEE Internet of Things Journal
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2023-09-01
Volume
10
Issue
17
Pages
14965-14987
ISSN
  • 2327-4662 (ISSN-L)
  • 2372-2541
DOI
10.1109/jiot.2023.3263909
OpenAlex
W4362514681
Semantic Scholar
bc0b2c5033fdf66b5f48adf715dd333f94f9064d
Cited by
357
References
139
Citations by year
2026: 113 · 2025: 127 · 2024: 88 · 2023: 26
FWCI
39.32
Type
journal article
Language
en
Open access
Licence
Locations
  • IEEE Internet of Things Journal (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • Figshare (submittedVersion, cc-by-nc-sa)
  • arXiv (Cornell University)
Funders
  • NSFC (U22A2029, U20A20175, 62101429)
  • Fundamental Research Funds for the Central Universities
Topics
  • Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
  • Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
  • Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
Keywords
digital twin, digital twin architecture, security threats, privacy, cyber-physical systems, distributed architecture, information-centric networking, semantic communication, security defenses, enabling technologies

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