摘要
随着车辆智能技术的发展,网络与车辆的结合成为了必然,给人们带来了极大的便利。同时,黑客还可以利用技术漏洞攻击车辆,从而导致严重的交通事故。基于这种情况,车辆信息安全保护技术逐渐成为人们关注的焦点。面对层出不穷的车联网网络攻击,需要态势感知对车联网进行保驾护航,为了提高车联网安全态势感知的准确度,文中提出了基于决策树的车联网安全态势预测模型,由于网络攻击往往由某些特定的属性发生异常变化,属性变化的过程就是一种攻击方式,决策树根据这些属性分类,使用信息增益率来构建决策树,并推导出决策的规则。通过实验验证了所提算法在车联网安全态势感知中的可行性以及预测结果的准确性。
With the development of vehicle intelligent technology,the combination of network and vehicle becomes inevitable,which brings great convenience to people.At the same time,hackers can also use technical loopholes to attack vehicles,resulting in serious traffic accidents and even vehicle crashes.Based on this situation,vehicle information security technology has gradually become the focus of attention.In the face of endless network attacks on Internet of vehicles,situation awareness is needed to protect the Internet of vehicles.In order to improve the accuracy of IOV security situation awareness,this paper proposes a decision tree-based IOV security situation prediction model.Because network attacks often change abnormally by certain specific attri-butes,the process of attribute change is an attack method.The tree is classified according to these attributes,the information gain rate is used to build a decision tree,and the rules for decision are derived.Through experiments,the feasibility of the proposed algorithm in the security situation awareness of the Internet of Vehicles and the accuracy of the prediction results are verified.
作者
唐亮
李飞
TANG Liang;LI Fei(School of Cybersecurity,Chengdu University of Information Technology,Chengdu 610225,China)
出处
《计算机科学》
CSCD
北大核心
2021年第S01期514-517,共4页
Computer Science
基金
四川省自然科学基金(2019YFG0201)
成都市科技项目(2018-YF05-00707-SN)。
关键词
车联网安全
态势感知
决策树
Internet of vehicles security
Situation awareness
Decision tree
