CEAP: SVM-based intelligent detection model for clustered vehicular ad hoc networks

作者：

Highlights：

• Proposing an intelligent detection model for clustered VANETs using SVM.

• The proposed detection model reduces the training set size of the SVM classifier.

• The proposed detection model is able to operate in highly mobile environments.

• We simulate the model using different kernel functions of SVM to select the best.

• We study the scalability w.r.t the number of vehicles and percentage of malicious nodes.

摘要

•Proposing an intelligent detection model for clustered VANETs using SVM.•The proposed detection model reduces the training set size of the SVM classifier.•The proposed detection model is able to operate in highly mobile environments.•We simulate the model using different kernel functions of SVM to select the best.•We study the scalability w.r.t the number of vehicles and percentage of malicious nodes.

论文关键词：Vehicular ad hoc network,Intrusion detection,High mobility,Support vector machine (SVM),Malicious node,Training set size reduction

论文评审过程：Received 18 April 2015, Revised 28 September 2015, Accepted 10 December 2015, Available online 23 December 2015, Version of Record 11 January 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.12.006