基于车辆行驶模型的Sybil攻击检测算法

Sybil Attack Detection Based on Vehicle Driving Pattern Based

Sybil攻击通过在网络内伪造多个身份,扰乱网络内节点间的通信,影响了车联网(Vehicular Ad hoc Networks,VANET)性能。为此,提出基于车辆行驶模型的Sybil攻击检测(VehicleDriving Pattern based Sybil Attack Detection,VDP-SAD)算法。VDP-SAD算法依据Beacon消息为每辆车构建行驶模型矩阵(Driving Pattern Matrix,DPM),再计算DPM的特征值,利用特征值评估车辆行驶模型的相似性,检测Sybil攻击节点。仿真结果表明,VDP-SAD算法具有较高的检测率。

Sybil attack forges false identities in the network to disrupt compromise the communication amongthe network nodes,and it affects the performance of Vehicular Ad hoc Networks(VANETs).Therefore,vehicle driving pattern based sybil attack detection(VDP-SAD)is proposed in this paper.In the VDP-SAD,driving pattern matrix(DPM)isconstructed for each vehicle based on the beaconing messages they communicate.Then,the eigenvalues of DPM are calculated,and the similarity of vehicle driving model is evaluated by eigenvalues,so as to detect Sybil attack nodes.Simulation results show that the proposed VDP-SAD algorithm has a high detection rate.