检索结果-南通市图书馆

Blockchain Driven Metaheuristic Route Planning in Secure Vehicular Adhoc Networks

Computers, Materials & Continua 2022年第12期73卷 6461-6477页

作者： Siwar Ben Haj Hassine Saud SAlotaibi Hadeel Alsolai Reem Alshahrani Lilia Kechiche Mrim M.Alnfiai Amira Sayed A.Aziz Manar Ahmed Hamza Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Sciences and Technology Taif UniversityTaif P.O.Box 11099Taif21944Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif P.O.Box 11099Taif21944Saudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Nowadays,vehicular ad hoc networks(VANET)turn out to be a core portion of intelligent transportation systems(ITSs),that mainly focus on achieving continual Internet connectivity amongst vehicles on the *** VANET was utilized to enhance driving safety and build an ITS in modern *** safety is a main portion of VANET,the privacy and security of these messages should be *** this aspect,this article presents a blockchain with sunflower optimization enabled route planning scheme(BCSFO-RPS)for secure *** presented BCSFO-RPSmodel focuses on the identification of routes in such a way that vehicular communication is *** addition,the BCSFO-RPS model employs SFO algorithm with a fitness function for effectual identification of ***,the proposed BCSFO-RPS model derives an intrusion detection system(IDS)encompassing two processes namely feature selection and *** detect intrusions,correlation based feature selection(CFS)and kernel extreme machine learning(KELM)classifier is *** performance of the BCSFO-RPS model is tested using a series of experiments and the results reported the enhancements of the BCSFO-RPS model over other approaches with maximum accuracy of 98.70%.

关键词： VANET sunflower optimization machine learning blockchain intrusion detection

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：