[1]滕志军,李 梦,谷金亮,等.融合多指标的WSN动态信任评估预测模型[J].郑州大学学报(工学版),2023,44(03):78-84.[doi:10.13705/j.issn.1671-6833.2022.06.014]
　ENG Zhijun,LI Meng,GU Jinliang,et al.A Dynamic Trust Evaluation and Prediction Model for WSN Based on Multiple Indexes[J].Journal of Zhengzhou University (Engineering Science),2023,44(03):78-84.[doi:10.13705/j.issn.1671-6833.2022.06.014]
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融合多指标的WSN动态信任评估预测模型()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
44
期数:
2023年03期
页码:
78-84
栏目:
出版日期:
2023-04-30

文章信息/Info

Title:
A Dynamic Trust Evaluation and Prediction Model for WSN Based on Multiple Indexes
作者:
滕志军1; 2;  李 梦2;  谷金亮2;  于沥博2;  王继红1; 2
1．东北电力大学 现代电力系统仿真控制与绿色电能新技术教育部重点实验室，吉林 吉林 132012; 2．东北电力大 学 电气工程学院，吉林 吉林 132012

Author(s):
ENG Zhijun1; 2; LI Meng2; GU Jinliang2; YU Libo2; WANG Jihong1; 2
1.Northeast Electric Power University Modern Electric Power System Simulation Control and Green Energy New Technology Education Key Laboratory, Jilin and Jilin 132012, 2.School of Electrical Engineering, Northeast Electric Power University, Jilin Jilin 132012, School of Electrical Engineering, Northeast Electric Power University, Jilin Jilin 132012

关键词:
模糊综合评判;  贴近度理论;  无线传感器网络;  信任阈值
Keywords:
fuzzy comprehensive evaluation;  similarity measure theory;  wireless sensor network;  trust threshold
分类号:
TP273
DOI:
10.13705/j.issn.1671-6833.2022.06.014
文献标志码:
A
摘要:
针对无线传感器网络中恶意节点引发的安全问题，在贝叶斯信任模型基础上，引入信誉维护函数自适应 降低前期节点交互行为次数的影响，引入异常弱化因子，降低由网络自身故障所带来的节点异常行为的误检，结合 模糊评判方法进行直接信任计算，为提高推荐信任评估的可靠性，采用贴近度理论对不同的推荐节点赋予权重再 分配获取间接信任，为提高信任模型的检测精度，采用加权因子，由直接信任值以及间接信任中的变量共同确定综 合信任值的大小，借助自适应权值动态更新综合信任值，有效避免短时间内信任的迅速提升，并利用滑动时间窗对 综合信任值进行预测，搭建了融合多指标的 WSN 动态信任评估预测模型 FSEPM，将预测信任值与实际信任值的差 值与信任阈值相比较，以判定节点性质。仿真结果表明: 该信任评估模型可精确可靠评估节点之间的信任关系，能 够有效检测出网络中的恶意节点，提高网络的安全性。
Abstract:
To address the security problems caused by malicious nodes in wireless sensor networks, in this study, based on the Bayesian trust models, the adaptive reputation maintenance function was introduced to reduce the influence of the previous node and number of interaction, and the abnormal weakening factor was introduced to reduce the false detection of node by the abnormal behaviors caused by network faults, and combined with the fuzzy evaluation mechanism, to calculate direct trust. In order to improve the reliability of recommendation trust evaluation, the similarity measure theory was adopted to assign weight to different recommendation nodes and redistribute to obtain indirect trust. In order to improve the detection accuracy of the trust model, a weighted factor was adopted to determine the size of the comprehensive trust value jointly by variables in direct and indirect trust. Using the adaptive weighting dynamic updating comprehensive trust value, it could effectively avoid the rapid promotion of trust in a short time, and use the sliding time window to predict the comprehensive trust value. The WSN dynamic trust evaluation and prediction model integrating multiple indicators FSEPM was built. The difference between the predicted trust value and the actual trust value was compared with the trust threshold to judge the node property. Simulation results showed that the trust evaluation model could accurately and reliably evaluate the trust relationship between nodes, detect malicious nodes effectively, and improve the security of wireless sensor networks.

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更新日期/Last Update: 2023-05-09