摘要
为了有效降低传感器网络安全风险等级,提出了基于最小二乘支持向量机的传感器网络安全风险预测方法.收集传感器网络安全风险数据,采用最小二乘支持向量机对数据进行训练,建立风险预测模型,根据预测的网络安全风险等级值对传感器网络实施控制.结果表明,该方法的传感器网络安全风险预测误差较低,控制效果较为理想,可以为传感器网络的安全稳定通信提供保障.
In order to effectively reduce the security risk level of sensor networks,a security risk prediction method based on least squares support vector machine was proposed.Security risk data of sensor networks were collected,the least squares support vector machine was used to train the data and the risk prediction model was established.According to the predicted network security risk level,the sensor networks were controlled.The results show that the prediction error by the as-proposed method for the security risk of sensor networks is relatively lower,and the control effect is ideal to provide guaranty for the secure and stable communication of sensor network.
作者
程雨芊
程中鼎
CHENG Yu-qian;CHENG Zhong-ding(Information Office,Electrical and Information Engineering,Shandong University,Weihai 264209,China;School of Mechanical,Electrical and Information Engineering,Shandong University,Weihai 264209,China)
出处
《沈阳工业大学学报》
CAS
北大核心
2022年第5期558-564,共7页
Journal of Shenyang University of Technology
基金
山东省自然科学基金项目(ZR2019MF054).
关键词
最小二乘支持向量机
传感器网络
安全风险
预测控制
分布式组密钥
风险预测误差
控制效果
least squares support vector machine
sensor network
security risk
predictive control
distributed group key
risk predicted error
control effect
