文献类型：期刊文献

中文题名：舰船移动网络信息安全大数据集成模型

英文题名：Big data integration model of ship mobile network information security

作者：杨昌尧[1];袁展伍[2];翁云峰[3]

机构：[1]岭南师范学院基础教育学院,广东湛江524037;[2]广东海洋大学海洋工程学院,广东湛江524008;[3]中兴通信股份有限公司,广东深圳518000

年份：2021

期号：20

起止页码：172

中文期刊名：舰船科学技术

外文期刊名：Ship Science and Technology

收录：北大核心、北大核心2020

基金：广东省湛江市科技局非资助科技攻关项目(2020B01460)

语种：中文

中文关键词：移动网络;舰船;信息安全;大数据;集成;关联数据

外文关键词：mobile network;warship;information security;big data;integrate;associated data

中文摘要：移动网络是保障舰船作战能力发挥的关键,舰船任务量的剧增,使得移动网络信息呈"井喷式"增长,给安全大数据的获取与应用带来了较大的阻碍,由此,提出舰船移动网络信息安全大数据集成模型。基于正则表达式原理,半自动化地抽取并转换安全大数据,搭建数据关联关系并行发现框架,计算数据之间的相似度,确定BP神经网络算法的最佳权值,执行BP神经网络算法分类并融合安全大数据,从而实现舰船移动网络信息安全大数据的集成。实验数据显示:数据集成平均耗时趋于1 s,并低于最小限值,具备较好的实时性。

外文摘要：Mobile network is the key to ensure the combat capability of ships.The sharp increase of ship tasks makes the mobile network information grow "blowout",which brings great obstacles to the acquisition and application of secure big data.Therefore,the ship mobile network information security big data set model is proposed.Based on the principle of regular expression,the security big data is extracted and transformed semi automatically,the parallel discovery framework of data association relationship is built,the similarity between data is calculated,the optimal weight of BP neural network algorithm is determined,the BP neural network algorithm is implemented to classify and integrate the security big data,so as to realize the integration of ship mobile network information security big data.The experimental data show that the average time consumption of data integration tends to 1 s,which is lower than the minimum limit,and has good real-time performance.