Cited by 126IoT and Edge/Fog ComputingAccess Control and TrustInternet of Things and AI

An Intelligent Trust Cloud Management Method for Secure Clustering in 5G Enabled Internet of Medical Things

Open access
Yang, Liu, Yu, Keping, Yang, Simon X., Chakraborty, Chinmay, Lu, Yinzhi, Guo, Tan·2022·IEEE Transactions on Industrial Informatics

Abstract

5G edge computing enabled Internet of Medical Things (IoMT) is an efficient technology to provide decentralized medical services while device-to-device (D2D) communication is a promising paradigm for future 5G networks. To assure secure and reliable communication in 5G edge computing and D2D enabled IoMT systems, this article presents an intelligent trust cloud management method. First, an active training mechanism is proposed to construct the standard trust clouds. Second, individual trust clouds of the IoMT devices can be established through fuzzy trust inferring and recommending. Third, a trust classification scheme is proposed to determine whether an IoMT device is malicious. Finally, a trust cloud update mechanism is presented to make the proposed trust management method adaptive and intelligent under an open wireless medium. Simulation results demonstrate that the proposed method can effectively address the trust uncertainty issue and improve the detection accuracy of malicious devices.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1109/tii.2021.3128954

Cites

27 of 27 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Part of this paper’s reference list could not be split into single entries.

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Yang, L., Yu, K., Yang, S. X., Chakraborty, C., Lu, Y., & Guo, T.
Affiliations
  • Chongqing University of Posts and Telecommunications (CN)
  • Waseda University (JP)
  • University of Guelph (CA)
  • Birla Institute of Technology, Mesra (IN)
Venue
IEEE Transactions on Industrial Informatics
Published
2022-12
Volume
18
Issue
12
Pages
8864-8875
ISSN
  • 1551-3203 (ISSN-L)
  • 1941-0050
OpenAlex
W3215141990
Cited by
126
References
27
Citations by year
2026: 7 · 2025: 11 · 2024: 17 · 2023: 26 · 2022: 65
FWCI
12.11
Type
journal article
Language
en
Open access
Locations
  • IEEE Transactions on Industrial Informatics (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University) (cc-by)
Funders
  • National Natural Science Foundation of China (61801072)
  • Science and Technology Research Program of Chongqing Municipal Education Commission (KJQN202000641)
  • Natural Science Foundation of Chongqing (cstc2020jcyj-msxmX0636)
  • Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research (JP18K18044, JP21K17736)
Topics
  • Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
  • Social Sciences › Sociology and Political Science › Access Control and Trust
  • Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
Keywords
trust management, Internet of Medical Things, 5G edge computing, device-to-device communication, malicious device detection, trust classification, secure clustering

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review