吉林大学学报(理学版) ›› 2020, Vol. 58 ›› Issue (4): 937-943.

• 计算机科学 • 上一篇    下一篇

基于指标选择和加权融合的无线传感器网络安全风险评估

袁开银, 王峰   

  1. 河南财经政法大学 现代教育技术中心, 郑州 450046
  • 收稿日期:2019-04-10 出版日期:2020-07-26 发布日期:2020-07-16
  • 通讯作者: 袁开银 E-mail:kaiyin_yuan@126.com

Security Risk Assessment of Wireless Sensor NetworksBased on Index Selection and Weighted Fusion

YUAN Kaiyin, WANG Feng   

  1. Center of Modern Educational Technology, Henan University of Economics and Law, Zhengzhou 450046, China
  • Received:2019-04-10 Online:2020-07-26 Published:2020-07-16
  • Contact: YUAN Kaiyin E-mail:kaiyin_yuan@126.com

摘要: 为提高无线传感器网络安全风险评估的准确性, 提出一种基于指标选择和加权融合的无线传感器网络安全风险评估模型. 首先建立无线传感器网络安全风险评估的指标体系, 并采用灰色关联分析法选择一些对评估结果有重要贡献的指标; 然后根据关联度对重要的无线传感器网络安全风险评估指标进行加权, 采用支持向量机拟合无线传感器网络安全风险变化特点, 并引入粒子群优化算法优化支持向量机参数; 最后与其他模型进行对比测试, 测试结果表明, 该模型获得了比对比模型更优的无线传感器网络安全风险评估结果, 评估正确率超过95%, 且提升了无线传感器网络安全风险评估效率.

关键词: 无线传感器网络, 风险评估, 指标体系, 指标贡献率, 灰色关联分析法, 粒子群优化算法

Abstract: In order to improve the accuracy of security risk assessment of wireless sensor network, we proposed a model of security risk assessment of wireless sensor network based on index selection and weighted fusion. Firstly, the index system of security risk assessment of wireless sensor network was established, and some indexes with important contribution were selected by grey relation analysis method. Secondly, according to the correlation degree, the security risk assessment indexes of important wireless sensor network were weighted,  support vector machine was used to fit the characteristics of security risk change of wireless sensor network, and particle swarm optimization algorithm was introduced to optimize the parameters of support vector machine. Finally, the results were compared with other models. The results show that the proposed model obtains better security risk evaluation results than the comparison model. The accuracy of the assessment is more than 95%, and the efficiency of the security risk assessment of wireless sensor networks is improved.

Key words: wireless sensor network, risk assessment, index system, index contribution rate, grey relation analysis method, particle swarm optimization algorithm

中图分类号: 

  • TP391