Method for detecting collusion attack node in road condition information sharing based on reputation point

Shichang XUAN; Hao TANG; Wu YANG

doi:10.11959/j.issn.1000-436x.2021051

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Method for detecting collusion attack node in road condition information sharing based on reputation point

Papers | 更新时间：2024-06-05

- Method for detecting collusion attack node in road condition information sharing based on reputation point
- Journal on Communications Vol. 42, Issue 4, Pages: 158-168(2021)
- 作者机构：
  
  哈尔滨工程大学信息安全研究中心，黑龙江哈尔滨 150001
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61802086);The Fundamental Research Funds for the Central Universities(3072020CF0601)
- DOI：10.11959/j.issn.1000-436x.2021051
  CLC： TP39
- Online First：2021-04，
  
  Published：25 April 2021
- 稿件说明：
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Shichang XUAN, Hao TANG, Wu YANG. Method for detecting collusion attack node in road condition information sharing based on reputation point[J]. Journal on Communications, 2021, 42(4): 158-168.
DOI：

Shichang XUAN, Hao TANG, Wu YANG. Method for detecting collusion attack node in road condition information sharing based on reputation point[J]. Journal on Communications, 2021, 42(4): 158-168. DOI： 10.11959/j.issn.1000-436x.2021051.

摘要

针对车联网中共谋节点可能协同发布虚假路况信息，导致路况信息共享过程中消息真实性无法保证的问题，提出了一种基于信誉积分的路况信息共享中共谋攻击节点检测方法。在路况信息聚合过程中，设计了恶意信息检测算法，能够检测到共谋节点发布的虚假消息，保证系统中传递消息的真实准确。安全性评估和实验表明，相比于现有方案，该方法对共谋节点的检测效率更高，共谋节点数量占比适应场景更广泛。

Abstract

Aiming at the problem that on occasion of the release of false road condition information by collusion nodes in the Internet of vehicles collaboratively

message authenticity could not be guaranteed in the process of road condition information sharing

a method for detecting collusion attack nodes in road condition information sharing based on reputation points was proposed.In the process of road condition information aggregation

a malicious information detection algorithm was designed to detect false messages issued by colluding nodes

which could ensure the authenticity and accuracy of messages delivered in the system.Experimental results show that the proposed method has higher detection efficiency for collusion nodes and adaption to a proportion of collusion nodes through security evaluation and experiments in comparison with the existing schemes.

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references

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