首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于超极特征匹配机制的人工网络安全流量 过滤算法研究
引用本文:吴昊.基于超极特征匹配机制的人工网络安全流量 过滤算法研究[J].井冈山大学学报(自然科学版),2019,40(5):46-51.
作者姓名:吴昊
作者单位:滁州职业技术学院信息工程系,安徽,滁州 239000
基金项目:2018年度校级科研立项课题(YJZ-2018-11)
摘    要:为解决当前物联网部署过程中存在的流量过滤效率低、传输受限等难题,提出了一种基于超极特征匹配机制的人工网络安全流量过滤算法。首先,基于能量最优原则,并针对sink节点与准分区节点之间的应答响应关系,构建一种网络初始化方案,使用分组问答-响应方式建立节点拓扑初始化关系并进行能量排序,实现网络快速建立及拓扑收敛。随后,综合考虑能量冗余、距离等超级特征并进行区域匹配,通过设计更新周期方法实现对区域节点稳态化控制,稳定区域传输质量,提高算法在超宽带传输条件下的适应能力。最后,采取扫描方式进行分区节点二次筛选,选取转发代价最小的分区节点进行组网,降低分区节点因能量受限而出现瘫痪的概率,进一步稳定算法对流量的过滤及传输质量。仿真实验表明:与当前常用的超宽带一体化传输过滤稳定算法(Ultra Wideband Integrated Transmission Filter Stabilization Algorithms,UWITFS算法)及分区流量综合过滤算法(Partition Flow Comprehensive Filtering Algorithms,PFCF算法)相比,所提算法具有流量过滤强度高、超宽带传输能力强的特性,实际部署价值较高。

关 键 词:物联网  超级特征匹配  超宽带  稳态传输  流量过滤
收稿时间:2019/4/8 0:00:00
修稿时间:2019/6/25 0:00:00

THE RESEARCH ON ARTIFICIAL NETWORK SECURITY TRAFFIC FILTERING ALGORITHMS BASED ON SUPERPOLE FEATURE MATCHING MECHANISM
WU Hao.THE RESEARCH ON ARTIFICIAL NETWORK SECURITY TRAFFIC FILTERING ALGORITHMS BASED ON SUPERPOLE FEATURE MATCHING MECHANISM[J].Journal of Jinggangshan University(Natural Sciences Edition),2019,40(5):46-51.
Authors:WU Hao
Institution:Department of Information Engineering, Chuzhou Vocational and Technical College, Chuzhou, Anhui 239000, China
Abstract:In order to solve the problems of low filtering efficiency and transmission constraints in the current deployment of the Internet of Things, an artificial network security flow filtering algorithm based on hyperpolar feature matching mechanism is proposed. Firstly, based on the principle of energy optimization and the response relationship between sink nodes and quasi-partitioned nodes, a network initialization scheme is constructed. The node topology initialization relationship is established by grouping question-answer-response method and the energy sequencing is carried out to achieve the rapid network establishment and topology convergence. Subsequently, the super-features such as energy redundancy and distance are considered comprehensively and the region matching is carried out. By designing the update cycle method, the steady-state control of regional nodes is realized, the quality of regional transmission is stabilized, and the adaptability of the algorithm under UWB transmission conditions is improved. Finally, the scanning mode is adopted to screen the partition nodes twice, and the least forwarding cost is selected to organize the network, which reduces the probability of the partition nodes being paralyzed due to energy constraints, and further stabilizes the filtering and transmission quality of the algorithm. The simulation results show that compared with Ultra Wideband Integrated Transmission Filter Stabilization Algorithms (UWITFS) and Partition Flow Comprehensive Filtering Algorithms (PFCF), the proposed algorithm has high flow filtering strength and strong UWB transmission capability. The actual deployment value is high because of its characteristics.
Keywords:Internet of Things  super feature matching  UWB  steady-state transmission  slow filtering
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《井冈山大学学报(自然科学版)》浏览原始摘要信息
点击此处可从《井冈山大学学报(自然科学版)》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号