A cross-domain trust inferential transfer model for cross-domain Industrial Internet of Things

被引:1
|
作者
Wu, Xu [1 ]
Liang, Junbin [2 ]
机构
[1] Hainan Normal Univ, Sch Informat Sci & Technol, Haikou, Peoples R China
[2] Guangxi Univ, Sch Comp Elect & Informat, Nanning, Peoples R China
来源
ICT EXPRESS | 2023年 / 9卷 / 05期
基金
中国国家自然科学基金;
关键词
Cross-domain; Collaboration service; Normal distribution; Trust computing; Industrial Internet of Things; MANAGEMENT MECHANISM; PROTOCOL; ROBUST; IOT;
D O I
10.1016/j.icte.2023.08.009
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Trust systems have been widely studied in Internet of Things (IoT). However, there is a little work done on trust management in cross-domain Industrial Internet of Things (IIoT). Many of these models focus mainly or only on trust management in a single administrative domain where trust is evaluated based on the same criteria. In general, different administrative domains adopt different trust models and trust evaluation standards. Due to different trust evaluation standards, trust values from different administrative domain cannot be compared, directly. Therefore, there is a need for a well-defined trust computing scheme for such multi-domain IIoT environment. This paper focuses on the research of cross-domain trust and proposes a cross-domain trust computing scheme "CDTCS", where trust recommendation value for an IIoT device in a domain can be transferred to a corresponding value in another domain. We analyze CDTCS performance in terms of trust accuracy and resiliency against attacks.(c) 2023 The Author(s). Published by Elsevier B.V. on behalf of The Korean Institute of Communications and Information Sciences. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:761 / 768
页数:8
相关论文
共 50 条
  • [31] Domain-Oriented Knowledge Transfer for Cross-Domain Recommendation
    Zhao, Guoshuai
    Zhang, Xiaolong
    Tang, Hao
    Shen, Jialie
    Qian, Xueming
    IEEE TRANSACTIONS ON MULTIMEDIA, 2024, 26 : 9539 - 9550
  • [32] Cross-Domain Kernel Induction for Transfer Learning
    Chang, Wei-Cheng
    Wu, Yuexin
    Liu, Hanxiao
    Yang, Yiming
    THIRTY-FIRST AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2017, : 1763 - 1769
  • [33] AutoTransfer: Instance Transfer for Cross-Domain Recommendations
    Gao, Jingtong
    Zhao, Xiangyu
    Chen, Bo
    Yan, Fan
    Guo, Huifeng
    Tang, Ruiming
    PROCEEDINGS OF THE 46TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL, SIGIR 2023, 2023, : 1478 - 1487
  • [34] Transfer learning in cross-domain sequential recommendation
    Xu, Zitao
    Pan, Weike
    Ming, Zhong
    INFORMATION SCIENCES, 2024, 669
  • [35] TLRec: Transfer Learning for Cross-domain Recommendation
    Chen, Leihui
    Zheng, Jianbing
    Gao, Ming
    Zhou, Aoying
    Zeng, Wei
    Chen, Hui
    2017 IEEE INTERNATIONAL CONFERENCE ON BIG KNOWLEDGE (IEEE ICBK 2017), 2017, : 167 - 172
  • [36] Gait recognition with cross-domain transfer networks
    Tong, Suibing
    Fu, Yuzhuo
    Ling, Hefei
    JOURNAL OF SYSTEMS ARCHITECTURE, 2019, 93 : 40 - 47
  • [37] Boosted Multifeature Learning for Cross-Domain Transfer
    Yang, Xiaoshan
    Zhang, Tianzhu
    Xu, Changsheng
    Yang, Ming-Hsuan
    ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2015, 11 (03)
  • [38] Graph Enabled Cross-Domain Knowledge Transfer
    Yao, Shibo
    ProQuest Dissertations and Theses Global, 2022,
  • [39] Trust and Distrust based Cross-domain Recommender System
    Richa
    Bedi, Punam
    APPLIED ARTIFICIAL INTELLIGENCE, 2021, 35 (04) : 326 - 351
  • [40] Exploiting Trust and Usage Context for Cross-Domain Recommendation
    Xu, Zhenzhen
    Zhang, Fuli
    Wang, Wei
    Liu, Haifeng
    Kong, Xiangjie
    IEEE ACCESS, 2016, 4 : 2398 - 2407