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Cited by 110Vehicular Ad Hoc Networks (VANETs)Access Control and TrustSecurity in Wireless Sensor Networks

Decentralized Trust Evaluation in Vehicular Internet of Things

Open access
Guleng, Siri, Wu, Celimuge, Chen, Xianfu, Wang, Xiaoyan, Yoshinaga, Tsutomu, Ji, Yusheng·2019·IEEE Access
DOI 10.1109/access.2019.2893262
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Abstract

Trust management in a decentralized vehicular network, such as vehicular ad hoc network, is particularly challenging due to the lack of centralized communication infrastructure and a fast varying feature of the vehicular environment. In this paper, we propose a decentralized trust management scheme for vehicular networks. The proposed scheme uses a fuzzy logic-based trust calculation approach to evaluate the direct trust where trustee nodes are located within the transmission range of a trustor node. A reinforcement learning-based approach is also employed to estimate the indirect trust where the behaviors of trustee cannot be observed directly. The extensive simulations are conducted to show the advantage of the proposed scheme over other baseline approaches.

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  • Rani et al. used game theory to design a lightweight trust evaluation scheme, improving malicious node detection success rate and energy efficiency, but the types of external attacks resisted are relatively single and protection comprehensiveness is poor.

    “In the same year, Rani R and others [50] used game theory to design a lightweight trust evaluation scheme, which not only improved the success rate of malicious node detection but also improved the energy efficiency of trust evaluation.However, the types of external attacks that can be resisted are relatively single, and the comprehensiveness of the protection of trust assessment is relatively”

    From A Survey on Zero Trust Architecture: Challenges and Future Trends (2022) · cites this paper as [50]

    Split into 2 atoms — 0 confirmed, 1 partially supported, 1 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

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  • Guleng et al. proposed a decentralized fuzzy-logic architecture integrating a vehicle's own experience and peer recommendations to label unintentional dishonest behavior, using reinforcement learning and Q-learning for indirect trust.

    “In [115], Guleng et al. proposed a decentralized architecture that integrates a vehicle’s own experience and peer recommendations using fuzzy logic. This is carried out with the intention of labeling the vehicle’s unintentional dishonest behavior. The concept of RL is enforced by an indirect trust score for vehicles with no direct connection to the trustor.”

    From Security and Trust Management in the Internet of Vehicles (IoV): Challenges and Machine Learning Solutions (2024) · cites this paper as [115]

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Research works printed but not linked: 26

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  26. CELIMUGE WU received the M.E. degree from the Beijing Institute of Technology, China, in 2006, and the Ph.D. degree from The Univer- sity of Electro-Communications, Japan, in 2010, where he is currently an Associate Professor with the Graduate School of Informatics and Engineer- ing. His current research interests include vehicu- lar ad hoc networks, sensor networks, intelligent transport systems, the Internet of Things, 5G, and mobile cloud computing. He is/has been a TPC Co-Chair of the Wireless Days 2019 and ICT-DM 2018 and a Track Co-Chair for many international conferences, including the ICCCN 2019 and the IEEE PIMRC 2016.

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Authors
Guleng, S., Wu, C., Chen, X., Wang, X., Yoshinaga, T., & Ji, Y.
Affiliations
  • Hohhot Minzu College (CN)
  • University of Electro-Communications (JP)
  • VTT Technical Research Centre of Finland (FI)
  • Ibaraki University (JP)
  • National Institute of Informatics (JP)
ORCID
Venue
IEEE Access
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2019
Volume
7
Pages
15980-15988
ISSN
2169-3536 (ISSN-L)
DOI
10.1109/access.2019.2893262
OpenAlex
W2909030650
Cited by
110
References
2
Citations by year
2026: 10 · 2025: 9 · 2024: 15 · 2023: 19 · 2022: 15 · 2021: 15 · 2020: 19 · 2019: 8
FWCI
5.12
Type
journal article
Language
en
Open access
Licence
ieeexplore.ieee.org/Xplorehelp/downloads/license-information/OAPA.html (vor)
Locations
  • IEEE Access (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • Inner Mongolia Science and Technology Major Project
  • National Institute of Informatics, Japan, through the Open Collaborative Research Program (FY2018)
  • Telecommunications Advanced Foundation
  • JSPS KAKENHI (16H02817, 16K00121, 17K12670)
Topics
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
  • Social Sciences › Sociology and Political Science › Access Control and Trust
  • Physical Sciences › Computer Science › Computer Networks and Communications › Security in Wireless Sensor Networks
Keywords
trust management, vehicular networks, vehicular Internet of Things, vehicular ad hoc networks, direct trust, indirect trust, reinforcement learning

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