基于CBR的车联网网络安全应急响应系统及方法  被引量:2

CBR-based Emergency Response System and Method for Internet of Vehicle Security

在线阅读下载全文

作  者:廖祖奇 李飞[1] 张鹏飞[1] LIAO Zu-qi;LI Fei;ZHANG Peng-fei(Chengdu University of Information Technology,Chengdu 610103,China)

机构地区:[1]成都信息工程大学,四川成都610103

出  处:《计算机与现代化》2020年第11期109-116,共8页Computer and Modernization

基  金:四川省自然科学基金资助项目(2016GZ0343,2018JY0510,18RKX0667)。

摘  要:随着车联网的快速发展,其安全问题日益突出,目前学术界主要的研究方向都在于具体终端的安全,并没有将车联网作为整体来进行安全研究,所以对于此方向的研究处于迫切之际。针对该问题,本文提出基于经验知识结构集(Set of Experience Knowledge Structure,SOEKS)和基于案例推理(Case-Based Reasoning,CBR)的车联网网络安全应急响应方法,来实现对具体安全事件的自动化快速处理。设计对车联网数据源以及案件的知识表示方法,并且设计基于最近邻算法的双重相似度匹配算法,来快速匹配安全事件,从而得到快速且较准确的响应。最后通过实现该应急响应系统,验证了该系统能够从历史数据中获得准确的当前事件的应急响应方案,验证了本文方法的可行性和有效性。With the rapid development of the Internet of vehicles,its security issues are increasingly prominent.At present,the main research direction of the academic community is the security of specific terminals,and the Internet of vehicles is not as a whole to carry out security research,so the research in this direction is in an urgent moment.To solve this problem,this paper proposes a network security emergency response method for the Internet of vehicles based on set of experience knowledge structure(SOEKS)and case-based reasoning(CBR)to realize the automatic and fast processing of specific security events.The paper designs the knowledge representation method for the data sources and cases of the Internet of vehicles,and designs a double similarity matching algorithm based on the nearest neighbor algorithm to quickly match the security events,so as to get a fast and more accurate response.Finally,the paper implements the emergency response system,verifies that the system can get accurate emergency response plan of current events from historical data,and confirms the feasibility and effectiveness of the method proposed in this paper.

关 键 词:车联网 网络安全 应急响应策略 匹配算法 CBR 

分 类 号:U495[交通运输工程—交通运输规划与管理] U463.67[交通运输工程—道路与铁道工程]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象