李勇, 陈牧, 马媛媛, 李尼格, 郭广鑫. 基于图模型和相似性计算的新型电力终端动态信任评估方法[J]. 电力信息与通信技术, 2024, 22(12): 62-68. DOI: 10.16543/j.2095-641x.electric.power.ict.2024.12.09
引用本文: 李勇, 陈牧, 马媛媛, 李尼格, 郭广鑫. 基于图模型和相似性计算的新型电力终端动态信任评估方法[J]. 电力信息与通信技术, 2024, 22(12): 62-68. DOI: 10.16543/j.2095-641x.electric.power.ict.2024.12.09
LI Yong, CHEN Mu, MA Yuanyuan, LI Nige, GUO Guangxin. A New Dynamic Trust Evaluation Method for Power Terminals Based on Graph Model and Similarity Calculation[J]. Electric Power Information and Communication Technology, 2024, 22(12): 62-68. DOI: 10.16543/j.2095-641x.electric.power.ict.2024.12.09
Citation: LI Yong, CHEN Mu, MA Yuanyuan, LI Nige, GUO Guangxin. A New Dynamic Trust Evaluation Method for Power Terminals Based on Graph Model and Similarity Calculation[J]. Electric Power Information and Communication Technology, 2024, 22(12): 62-68. DOI: 10.16543/j.2095-641x.electric.power.ict.2024.12.09

基于图模型和相似性计算的新型电力终端动态信任评估方法

A New Dynamic Trust Evaluation Method for Power Terminals Based on Graph Model and Similarity Calculation

  • 摘要: 针对新型电力系统海量终端的信任模型计算粒度粗、消耗资源大的问题,文章提出一种基于图模型和相似性计算的终端动态信任评估方法。首先通过建立图模型,结合模糊推理计算节点的直接信任,采用相似性度量方法计算间接信任,通过加权求和确定综合信任值的大小。然后采用自回归移动平均(auto-regressive moving average,ARMA)模型预测综合信任值,根据预测值、实际值的残差和历史阈值比较判断节点的性质。最后通过实验结果证明,该信任评估方法能够及时准确地发现和检测恶意终端节点。

     

    Abstract: The trust model for massive terminals has the problems of coarse computing granularity and high resource consumption. A new dynamic trust evaluation method for power terminals based on graph model and similarity calculation(GASTEM) is proposed. Firstly, by establishing a graph model and combining fuzzy reasoning to calculate the direct trust of nodes, using similarity measurement method to calculate indirect trust, and the size of the comprehensive trust value through weighted summation is determined. Then, the AMRA model is used to predict the comprehensive trust value. The properties of the node are determined by comparing the residuals of the predicted value, actual value, and historical threshold. Finally, the experimental results demonstrate that this trust evaluation method can timely and accurately discover and detect malicious terminal nodes.

     

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