摘要
针对物联网数据在传输过程中节点众多,传输量较大,无法实现实时检测供给,导致产生较多不确定性的融合节点信息,使物联网受到各种潜在性的安全隐患的问题,提出基于Prim算法的物联网安全数据融合信誉度模型。借助Prim算法及图例分析在加权连通图里优化最小生成树,将物理上采集邻近的节点信息归纳统计数据融合;在数据融合安全计算下,对传输过程中产生的恶意融合节点判断并计算其信誉度,实现安全数据融合信誉度模型构建。通过仿真可知,所提模型可以充分检测数据传输过程中不确定性,精准衡量融合结果,有效防止数据被恶意篡改,具有良好的安全性、真实性、可用性,且传输效率较高,在未来互联网行业发展中有巨大的应用前景。
This paper presents a credibility model of Internet of Things security data fusion based on the Prim algorithm for improving the security of the Internet of Things. The minimum spanning tree in the weighted connected graph was optimized by the analysis results of the Prim algorithm and legend, and the information of neighboring nodes collected physically was summarized and statistically fused. In the security computing of data fusion, the reputation of malicious fusion nodes generated in the transmission process was judged and calculated, thus achieving the construction of the credibility model of security data fusion. The results show that the model has excellent security, authenticity, availability, and high transmission efficiency, and has promising application prospects in the future development of the internet industry.
作者
韦晓敏
彭灿华
WEI Xiao-min;PENG Can-hua(Institute of Information Technology of Guet,Guangxi Guilin 541004,China)
出处
《计算机仿真》
北大核心
2022年第6期421-424,443,共5页
Computer Simulation
基金
2020年度广西高校中青年教师科研基础能力提升项目(2020KY57017)。
关键词
物联网
最小生成树
安全数据融合
信誉度模型
Internet of Things
Minimum spanning tree
Security data fusion
Reputation model
