• 中国精品科技期刊
  • CCF推荐A类中文期刊
  • 计算领域高质量科技期刊T1类
Advanced Search
Feng Jingyu, Yu Tingting, Wang Ziying, Zhang Wenbo, Han Gang, Huang Wenhua. An Edge Zero-Trust Model Against Compromised Terminals Threats in Power IoT Environments[J]. Journal of Computer Research and Development, 2022, 59(5): 1120-1132. DOI: 10.7544/issn1000-1239.20211129
Citation: Feng Jingyu, Yu Tingting, Wang Ziying, Zhang Wenbo, Han Gang, Huang Wenhua. An Edge Zero-Trust Model Against Compromised Terminals Threats in Power IoT Environments[J]. Journal of Computer Research and Development, 2022, 59(5): 1120-1132. DOI: 10.7544/issn1000-1239.20211129

An Edge Zero-Trust Model Against Compromised Terminals Threats in Power IoT Environments

Funds: This work was supported by the National Natural Science Foundation of China (62102312) and the Science and Technology Project of State Grid Co., Ltd. (J2021206).
More Information
  • Published Date: April 30, 2022
  • With the continuous penetration of information technology into the power industry, the exposure of power IoT networks has been further increased. Attackers can use compromised terminals as the springboard to infiltrate the network, and thus stealing sensitive data or doing damage in the power industry system. Aiming at the bottleneck of zero-trust centralized deployment of massive power terminals access, an edge zero-trust model is proposed. Around the dense power terminals, zero-trust engine should be deployed in manner of distributed multi- points. Trust factors are collected in real time and stored on the blockchain. By maintaining a consortium blockchain called TF_chain, the storage edge servers can synchronously share trust factors generated by power terminals on the move, and thus facilitating traceability and preventing tampering. The abnormal and sensitive factors are extracted to carry out dynamic trust evaluation. The trust value can be rapidly attenuated by the sudden behaviors of compromised terminals, so as to fast prevent their threats during the authentication. A lightweight signcryption method is adopted to ensure the security of authentication information transmitted from edge to cloud. The simulation results show that the proposed model can disperse the zero-trust processing load of centralized deployment and effectively fight against compromised terminals threats under the condition of marginal deployment.
  • Related Articles

    [1]Deng Qingyong, Zuo Qinghua, Li Zhetao, Wang En, Guo Bin. Privacy-Preserving Bilateral Reputation Evaluation in Blockchain Based Crowdsensing[J]. Journal of Computer Research and Development, 2024, 61(11): 2681-2692. DOI: 10.7544/issn1000-1239.202440302
    [2]Liu Wei, Tang Congke, Ma Jie, Tian Zhao, Wang Qi, She Wei. A Federated Learning Model for Privacy Protection Based on Blockchain and Dynamic Evaluation[J]. Journal of Computer Research and Development, 2023, 60(11): 2583-2593. DOI: 10.7544/issn1000-1239.202330269
    [3]Ran Jinhao, Cai Dongliang. Attribute Signature Identity Authentication Scheme Based on Blockchain and Trusted Execution Environment[J]. Journal of Computer Research and Development, 2023, 60(11): 2555-2566. DOI: 10.7544/issn1000-1239.202330268
    [4]Zhong Lujie, Wang Mu. Blockchain-Enpowered Cooperative Resource Allocation Scheme for Computing First Network[J]. Journal of Computer Research and Development, 2023, 60(4): 750-762. DOI: 10.7544/issn1000-1239.202330002
    [5]Zhang Zelin, Wang Huaqun. Dynamic Key Management of Industrial Internet Based on Blockchain[J]. Journal of Computer Research and Development, 2023, 60(2): 386-397. DOI: 10.7544/issn1000-1239.202111095
    [6]Zhou Wei, Wang Chao, Xu Jian, Hu Keyong, Wang Jinlong. Privacy-Preserving and Decentralized Federated Learning Model Based on the Blockchain[J]. Journal of Computer Research and Development, 2022, 59(11): 2423-2436. DOI: 10.7544/issn1000-1239.20220470
    [7]Liu Feng, Yang Jie, Li Zhibin, Qi Jiayin. A Secure Multi-Party Computation Protocol for Universal Data Privacy Protection Based on Blockchain[J]. Journal of Computer Research and Development, 2021, 58(2): 281-290. DOI: 10.7544/issn1000-1239.2021.20200751
    [8]Huang Kezhen, Lian Yifeng, Feng Dengguo, Zhang Haixia, Liu Yuling, Ma Xiangliang. Cyber Security Threat Intelligence Sharing Model Based on Blockchain[J]. Journal of Computer Research and Development, 2020, 57(4): 836-846. DOI: 10.7544/issn1000-1239.2020.20190404
    [9]Ren Yanbing, Li Xinghua, Liu Hai, Cheng Qingfeng, Ma Jianfeng. Blockchain-Based Trust Management Framework for Distributed Internet of Things[J]. Journal of Computer Research and Development, 2018, 55(7): 1462-1478. DOI: 10.7544/issn1000-1239.2018.20180073
    [10]Yu Hui, Zhang Zongyang, Liu Jianwei. Research on Scaling Technology of Bitcoin Blockchain[J]. Journal of Computer Research and Development, 2017, 54(10): 2390-2403. DOI: 10.7544/issn1000-1239.2017.20170416
  • Cited by

    Periodical cited type(8)

    1. 钱忠胜,黄恒,朱辉,刘金平. 融合层注意力机制的多视角图对比学习推荐方法. 计算机研究与发展. 2025(01): 160-178 . 本站查看
    2. 钱忠胜,肖双龙,朱辉,王晓闻,刘金平. 利用GRU双分支信息协同增强的长尾推荐模型. 计算机科学与探索. 2025(02): 476-489 .
    3. 黄康鹏,冯锋. 基于一维卷积神经网络的序列推荐算法. 计算机技术与发展. 2025(03): 172-178 .
    4. 黄玲,黄镇伟,黄梓源,关灿荣,高月芳,王昌栋. 图卷积宽度跨域推荐系统. 计算机研究与发展. 2024(07): 1713-1729 . 本站查看
    5. 张惠鹃,黄钦阳,胡诗彦,杨青,张敬伟. 完全图高阶关系驱动的链接预测. 计算机研究与发展. 2024(07): 1825-1835 . 本站查看
    6. 张劲羽,马晨曦,李超,赵中英. 基于三分支图外部注意力网络的轻量化跨域序列推荐. 计算机研究与发展. 2024(08): 1930-1944 . 本站查看
    7. 朱明朔,沈苏彬. 一种基于因果推断的序列推荐模型. 计算机技术与发展. 2024(09): 102-108 .
    8. 陈万志,王军. 时间感知增强的动态图神经网络序列推荐算法. 计算机工程与应用. 2024(20): 142-152 .

    Other cited types(20)

Catalog

    Article views (277) PDF downloads (170) Cited by(28)

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return