VANET中位置相关的轻量级Sybil攻击检测方法

辛燕; 冯霞; 李婷婷

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

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VANET中位置相关的轻量级Sybil攻击检测方法

学术论文 | 更新时间：2024-06-05

- VANET中位置相关的轻量级Sybil攻击检测方法
- Position related lightweight Sybil detection approach in VANET
- 通信学报 2017年38卷第4期页码：110-119
- 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：
  
  [ "辛燕（1978-），女，江苏泰兴人，江苏大学博士生，主要研究方向为车联网安全。" ]
  [ "冯霞（1983-），女，江苏扬中人，安徽大学博士生，主要研究方向为车联网与交通大数据安全。" ]
  [ "李婷婷（1993-），女，江苏南通人，江苏大学硕士生，主要研究方向为车联网安全与隐私保护。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61472001);江苏省重点研发计划基金资助项目(BE2015136)
- DOI：10.11959/j.issn.1000-436x.2017055
  中图分类号： TP393
- 网络出版日期：2017-04，
  
  纸质出版日期：2017-04-25
- 稿件说明：
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辛燕, 冯霞, 李婷婷. VANET中位置相关的轻量级Sybil攻击检测方法[J]. 通信学报, 2017,38(4):110-119.

Yan XIN, Xia FENG, Ting-ting LI. Position related lightweight Sybil detection approach in VANET[J]. Journal on communications, 2017, 38(4): 110-119.
辛燕, 冯霞, 李婷婷. VANET中位置相关的轻量级Sybil攻击检测方法[J]. 通信学报, 2017,38(4):110-119. DOI： 10.11959/j.issn.1000-436x.2017055.

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

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