电子科技大学学报
電子科技大學學報
전자과기대학학보
JOURNAL OF UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA
2013年
4期
586-591
,共6页
徐会彬%施星君%任斌%薛小平
徐會彬%施星君%任斌%薛小平
서회빈%시성군%임빈%설소평
最小二乘法%位置验证%漏警率%虚警率%运动轨迹%VANETs
最小二乘法%位置驗證%漏警率%虛警率%運動軌跡%VANETs
최소이승법%위치험증%루경솔%허경솔%운동궤적%VANETs
least square method%location verification%false negative rate%false positive rate%trajectory%VANETs
正确的位置信息在维护VANETs的正常运行扮演着重要的角色,恶意节点的位置欺骗将严重影响VANETs诸多应用。通过对节点的位置验证以检测节点的位置欺骗是VANETs重要的研究领域。针对VANETs中车辆移动的相对速度较高,网络拓扑结构频繁变化,传统WSN和MANET中的位置验证方案不再适用于VANETs,提出基于车辆的运动轨迹位置验证方案,采用最小二乘法对车辆进行连续定位跟踪,并绘制其行驶路线,与邻居车辆的行驶路线、速度相比较,计算其吻合度,检测位置欺骗。仿真结果表明,该方案有较低的漏警率和虚警率,当恶意节点的欺骗距离达到30 m时,漏警率和虚警率接近于0。
正確的位置信息在維護VANETs的正常運行扮縯著重要的角色,噁意節點的位置欺騙將嚴重影響VANETs諸多應用。通過對節點的位置驗證以檢測節點的位置欺騙是VANETs重要的研究領域。針對VANETs中車輛移動的相對速度較高,網絡拓撲結構頻繁變化,傳統WSN和MANET中的位置驗證方案不再適用于VANETs,提齣基于車輛的運動軌跡位置驗證方案,採用最小二乘法對車輛進行連續定位跟蹤,併繪製其行駛路線,與鄰居車輛的行駛路線、速度相比較,計算其吻閤度,檢測位置欺騙。倣真結果錶明,該方案有較低的漏警率和虛警率,噹噁意節點的欺騙距離達到30 m時,漏警率和虛警率接近于0。
정학적위치신식재유호VANETs적정상운행분연착중요적각색,악의절점적위치기편장엄중영향VANETs제다응용。통과대절점적위치험증이검측절점적위치기편시VANETs중요적연구영역。침대VANETs중차량이동적상대속도교고,망락탁복결구빈번변화,전통WSN화MANET중적위치험증방안불재괄용우VANETs,제출기우차량적운동궤적위치험증방안,채용최소이승법대차량진행련속정위근종,병회제기행사로선,여린거차량적행사로선、속도상비교,계산기문합도,검측위치기편。방진결과표명,해방안유교저적루경솔화허경솔,당악의절점적기편거리체도30 m시,루경솔화허경솔접근우0。
The correct location information of vehicles plays an important role in the maintenance of the normal operation of vehicle Ad-hoc networks (VANETs) and the position spoofing from malicious node will seriously affect many applications of VANETs. Therefore, the detection of the position spoofing by location verification is an important issue. The traditional location algorithm in WSN and MANET no longer applies to VANETs. In this paper, a vehicle trajectory-based location verification scheme is proposed to locate and track continuously the vehicle and draw the trajectory. The inosculation is calculated and the position spoofing is detected by comparing with the trajectory and speed of the neighbor vehicle. The simulation results show that false negative rate and false positive rate are low. When the cheating distance of malicious node is 30 m, false negative and false positive rate are close to 0.