VDCM:A Data Collection Mechanism for Crowd Sensing in Vehicular Ad Hoc Networks

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外文摘要：With the rapid development of mobile devices,aggregation security and efficiency topics are more important than past in crowd sensing.When collecting large-scale vehicle-provided data,the data transmitted via autonomous networks are publicly accessible to all attackers,which increases the risk of vehicle exposure.So we need to ensure data aggregation security.In addition,low aggregation efficiency will lead to insufficient sensing data,making the data unable to provide data mining services.Aiming at the problem of aggregation security and efficiency in large-scale data collection,this article proposes a data collection mechanism(VDCM)for crowd sensing in vehicular ad hoc networks(VANETs).The mechanism includes two mechanism assumptions and selects appropriate methods to reduce consumption.It selects sub mechanism 1 when there exist very few vehicles or the coalition cannot be formed,otherwise selects sub mechanism 2.Single aggregation is used to collect data in sub mechanism 1.In sub mechanism 2,cooperative vehicles are selected by using coalition formation strategy and auction cooperation agreement,and multi aggregation is used to collect data.Two sub mechanisms use Paillier homomorphic encryption technology to ensure the security of data aggregation.In addition,mechanism supplements the data update and scoring steps to increase the amount of available data.The performance analysis shows that the mechanism proposed in this paper can safely aggregate data and reduce consumption.The simulation results indicate that the proposed mechanism reduces time consumption and increases the amount of available data compared with existing mechanisms.

外文关键词：

vehicular ad hoc networks(VANETs)crowd sensingdata collectiondata aggregation security

作者：

Juli Yin、Linfeng Wei、Zhiquan Liu、Xi Yang、Hongliang Sun、Yudan Cheng、Jianbin Mai

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作者单位：

College of Cyber Security,Jinan University,Guangzhou 510632,China

Guangdong Provincial Key Laboratory of Cyber and Information Security Vulnerability Research,Guangzhou 510643,China

College of Information Science Technology,Jinan University,Guangzhou 510632

基金：

National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaGuangdong Province Science and Technology Planning ProjectGuangdong Basic and Applied Basic Research FoundationScience and Technology Program of Guangzhou of ChinaFundamental Research Funds for the Central UniversitiesFundamental Research Funds for the Central UniversitiesGuangdong Provincial Key Laboratory of Cyber and Information Security Vulnerability Research

项目编号：

6227219561802146KTP202000222019A151501101720220101042121621417216224022020B1212060081

出版年：

2023

DOI：

10.26599/BDMA.2022.9020041

大数据挖掘与分析(英文版)

CSCDEI

ISSN：

年,卷(期)：2023.6(4)

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