Position related lightweight Sybil detection approach in VANET

Yan XIN; Xia FENG; Ting-ting LI

doi:10.11959/j.issn.1000-436x.2017055

您当前的位置：

首页 >

文章列表页 >

Position related lightweight Sybil detection approach in VANET

Papers | 更新时间：2024-06-05

- Position related lightweight Sybil detection approach in VANET
- Journal on Communications Vol. 38, Issue 4, Pages: 110-119(2017)
- 作者机构：
  
  1. 江苏大学计算机科学与通信工程学院，江苏镇江 212013
  2. 安徽大学信息保障技术协同创新中心，安徽合肥 230601
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61472001);The Key Research and Development Project of Jiangsu Province(BE2015136)
- DOI：10.11959/j.issn.1000-436x.2017055
  CLC： TP393
- Online First：2017-04，
  
  Published：25 April 2017
- 稿件说明：
移动端阅览
Yan XIN, Xia FENG, Ting-ting LI. Position related lightweight Sybil detection approach in VANET[J]. Journal on Communications, 2017, 38(4): 110-119.
DOI：

Yan XIN, Xia FENG, Ting-ting LI. Position related lightweight Sybil detection approach in VANET[J]. Journal on Communications, 2017, 38(4): 110-119. DOI： 10.11959/j.issn.1000-436x.2017055.

摘要

在车联网中，同时使用多个虚假身份的 Sybil 攻击，在网络中散布虚假消息，都易造成资源的不公平使用和网络混乱。针对这一问题，提出快速识别车辆虚假位置的事件驱动型轻量级算法，当车辆出现在另一车辆的安全区域内，启动快速识别两车辆是否重叠的几何交叉模型（GCR

geometrical cross-recognition）算法，检测声称虚假位置的错误行为；同时，根据证实车辆收集的邻居范围内的局部车辆，建立位置偏差矩阵（PDM

position deviation matrix），进一步识别交叉车辆中的Sybil节点。性能分析和仿真实验表明，安全区域驱动下的轻量级算法识别速度快，检测率高，在车辆定位误差较低时性能更好；安全区域的引入也均衡了车辆密度过大时造成的通信负载影响，与同类算法相比，通信处理时延较低。

Abstract

In VANET

the Sybil attack simultaneously using multiple forged identities can easily cause the injustice of resource usage and make networks in a mess by distributing false messages.To solve this problem

an event-driven lightweight algorithm was proposed

which could identify vehicles false position quickly.When one vehicle appeared inside another's safety zone

a geometrical cross-recognition algorithm to calculate the overlap between vehicles to detect false position claiming was presented.At the same time

according to the neighbors within the confirming vehicle's radio range

position deviation matrix was established further to identify the Sybil node of two overlap vehicles.The performance analysis and simulation results show that the lightweight algorithm driven by safety zone demonstrates fast identification and high detection rate

especially when GPS error is very low.The imported safety zone can also balance the communication load impacting by heavy vehicular density.And the communication processing delay is lower than other approaches.

关键词

Keywords

references

HARTENSTEIN H , BOCHOW B , EBNER A , et al . Position-aware ad hoc wireless networks for inter-vehicle communications:the FleetNet project [C ] // ACM MobiHoc 2001 . 2001 : 259 - 262 .

ENKELMANN W , . FleetNet-applications for inter-vehicle communication [C ] // IEEE Intelligent Vehicles Symposium . 2003 : 162 - 167 .

MEJRI M N,BEN-OTHMAN J , HAMDI M . Survey on VANET security challenges and possible cryptographic solutions [J ] . Vehicular communications , 2014 , 1 ( 2 ): 53 - 66 .

TRULLOLS O , FIORE M , CASETTI C , et al . Planning roadside infrastructure for information dissemination in intelligent transportation systems [J ] . Computer Communications , 2010 , 33 ( 4 ): 432 - 442 .

GEORGIOS K , ONUR A , EYLEM E , et al . Vehicular networking:a survey and tutorial on requirements,architectures,challenges,standards and solutions [J ] . IEEE Communications Surveys and Tutorials , 2011 , 13 ( 4 ): 584 - 616 .

WAHAB O A , MOURAD A , OTROK H , et al . CEAP:SVM-based intelligent detection model for clustered vehicular ad hoc networks [J ] . Expert Systems with Applications , 2016 , 50 : 40 - 54 .

XIAO B , YU B , GAO C S . Detection and localization of Sybil nodes in VANETs [C ] // 2006 Workshop on Dependability Issues in Wireless Ad Hoc Networks and Sensor Networks . 2006 : 1 - 8 .

CHEN C , WANG X , HAN W L , et al . A robust detection of the Sybil attack in urban VANET [C ] // The 29th IEEE International Conference on Distributed Computing Systems Workshops (ICDCS 2009) . 2009 : 270 - 276 .

CHANG S , QI Y , ZHU H , et al . Footprint:detecting Sybil attacks in urban vehicular networks [J ] . IEEE Transactions on Parallel and Distributed Systems , 2012 , 23 ( 6 ): 1103 - 1114 .

SOYOUNG P , BABER A , DAMLA T , et al . Defense against Sybil attack in the initial deployment stage of vehicular ad hoc network based on roadside unit support [J ] . Security and Communication Networks , 2013 , 6 ( 4 ): 523 - 538 .

JIN D X , SONG J . A traffic flow theory aided physical measurement-based Sybil nodes detection mechanism in vehicular ad hoc networks [C ] // 2014 IEEE/ACIS 13th International Conference on Computer and Information Science . 2014 : 281 - 286 .

GUETTE G , DUCOURTHIAL B . On the Sybil attack detection in VANET [C ] // IEEE International Conference on Mobile Ad Hoc and Sensor Systems (MASS 2007) . 2007 : 1 - 6 .

YU B , XU C Z , XIAO B . Detection Sybil attacks in VANETs [J ] . Journal of Parrel and Distributed Computing , 2013 : 746 - 756 .

HICHEM S , MOHAMMED S S . An accurate and efficient collaborative intrusion detection framework to secure vehicular networks [J ] . Computers ＆ Electrical Engineering , 2015 , 43 ( c ): 33 - 47 .

GROVER J , GAUR M S , LAXMI V , et al . A Sybil attack detection approach using neighboring Vehicles in VANET [C ] // The 4th International Conference on Security of Information and Networks . 2011 : 151 - 158 .

GROVER J , LAXMI V , GAUR M S . Sybil attack detection in VANET using neighboring vehicles [J ] . International Journal of Security and Networks , 2014 , 9 ( 4 ): 222 - 233 .

SCHMIDT R K , LEINMUELLER T , SCHOCH E , et al . Vehicle behavior analysis to enhance security in VANETs [C ] // The 4th IEEE Vehicle-to-Vehicle Communications Workshop (V2VCOM2008) . 2008 : 1 - 8 .

STUEBING H , JAEGER A,BIßMEYER N , et al . Verifying mobility data under privacy considerations in Car-to-X communication [C ] // 17th ITS World Congress 2010 . 2010 : 1 - 12 .

RAMON B , JAVIER G , SORIANO S , et al . Road traffic congestion detection through cooperative vehicle-to-vehicle communications [C ] // 4th IEEE Workshop On User Mobility and Vehicular Networks (On-MOVE 2010) . 2010 : 606 - 612 .

KARNADI F K , MO Z H , LAN K . Rapid generation of realistic mobility models for VANET [C ] // Wireless Communications and Networking Conference . 2007 : 2506 - 2511 .

ETSI TS 102 637-2 V1.2.1.Specification of cooperative awareness basic service [S ] . 2011 .

李春彦 , 刘怡良 , 王良民 . 车载自组网基于交通场景的入侵行为检测机制 [J ] . 山东大学学报 , 2014 , 44 ( 1 ): 29 - 34 .

LI C Y , LIU Y L , WANG L M . Intrusion detection scheme based on traffic scenarios in vehicular ad hoc networks [J ] . Journal of Shandong University , 2014 , 44 ( 1 ): 29 - 34 .

ABUELENIN S M , ABUL-MAGD , et al . Effect of minimum headway distance on connectivity of VANET [J ] . Elsevier GmbH , 2015 , 69 ( 5 ): 867 - 871 .

BERLIN M A , MUTHUSUNDARI S . Safety distance calculation for collision avoidance in vehicular ad hoc networks [J ] . Scholars Journal of Engineering and Technology (SJET) , 2016 , 4 ( 1 ): 63 - 69 .

WEI Y W , GUAN Y . Lightweight location verification algorithms for wireless sensor networks [J ] . IEEE Transactions on Parallel and Distributed Systems , 2013 , 24 ( 5 ): 938 - 950 .

LABAYRADE R , ROYERE C , AUBERT D . Experimental assessment of the RESCUE collision-mitigation system [J ] . IEEE Transactions on Vehicular Technology , 2007 , 56 ( 1 ): 89 - 102 .

CHEN Y J , CHEN C C , WANG S N , et al . GPSenseCar-A collision avoidance support system using real-time GPS data in a mobile vehicular network [C ] // Second International Conference on Systems and Networks Communication . 2006 .

KAMRAN Z , MILOS B,MILOJEVIC , et al . Host-based intrusion detection for VANETs:a statistical approach to rogue node detection [J ] . IEEE Transactions on Vehicular Technology , 2016 , 65 ( 8 ): 6703 - 6714 .

KRAJZEWICZ D , HERTKORN G,RÖSSEL C , et al . SUMO (simulation of urban mobility):an open-source traffic simulation [C ] // 4th MESM . 2002 : 183 - 187 .

Views

1728

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Research on sybil attack in defense blockchain based on improved PBFT algorithm

New approach against Sybil attack in wireless sensor networks

Related Author

Yingxu LAI

Zunxu BO

Jing LIU

FENG Tao1

MA Jian-feng2

Related Institution

Faculty of Information Technology, Beijing University of Technology

Science and Technology on Information Assurance Laboratory

Engineering Research Center of Intelligent Perception and Autonomous Control,Ministry of Education

Shaanxi Key Laboratory of Network and System Security, Xidian University

School of Computer and Communication,Lanzhou University of Technology

AI问答

⁰