On Designing Collusion-Resistant Incentive Mechanisms for Mobile Crowdsensing Systems

Shiyu Ji, Tingting Chen
{"title":"On Designing Collusion-Resistant Incentive Mechanisms for Mobile Crowdsensing Systems","authors":"Shiyu Ji, Tingting Chen","doi":"10.1109/Trustcom/BigDataSE/ICESS.2017.233","DOIUrl":null,"url":null,"abstract":"With the tremendous popularity of smartphones and other portable devices, crowdsensing applications have become a center of attention in recent years. Different mechanisms have been designed to incentivize mobile users to participate in crowdsensing. However, there are still many open issues needed to be investigated for these incentive mechanisms. In this paper, we systematically study the collusion resistance issue for incentive mechanisms in crowdsensing applications. For a typical type of mobile crowdsensing scenarios, we have two theoretical findings, i.e., the criteria to determine whether an incentive mechanism can inherently resist the collusions with and without profit trading respectively. These criteria have direct practical benefits in screening potential incentive mechanisms for mobile crowdsensing. Furthermore, we also propose our solution that can resist any form of collusion attacks, even including profit trading among the attackers. We conduct extensive experiments to verify our theoretical results and evaluate the performance of our proposed mechanisms.","PeriodicalId":170253,"journal":{"name":"2017 IEEE Trustcom/BigDataSE/ICESS","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Trustcom/BigDataSE/ICESS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/Trustcom/BigDataSE/ICESS.2017.233","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

With the tremendous popularity of smartphones and other portable devices, crowdsensing applications have become a center of attention in recent years. Different mechanisms have been designed to incentivize mobile users to participate in crowdsensing. However, there are still many open issues needed to be investigated for these incentive mechanisms. In this paper, we systematically study the collusion resistance issue for incentive mechanisms in crowdsensing applications. For a typical type of mobile crowdsensing scenarios, we have two theoretical findings, i.e., the criteria to determine whether an incentive mechanism can inherently resist the collusions with and without profit trading respectively. These criteria have direct practical benefits in screening potential incentive mechanisms for mobile crowdsensing. Furthermore, we also propose our solution that can resist any form of collusion attacks, even including profit trading among the attackers. We conduct extensive experiments to verify our theoretical results and evaluate the performance of our proposed mechanisms.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
移动众测系统抗合谋激励机制设计研究
近年来,随着智能手机和其他便携式设备的广泛普及,众感应用成为人们关注的焦点。设计了不同的机制来激励手机用户参与众感。然而,这些激励机制仍有许多悬而未决的问题需要研究。本文系统地研究了众感应用中激励机制的抗合谋问题。对于一类典型的移动众感场景,我们分别得到了两个理论发现,即判断激励机制是否能够内在抵制有利润交易和无利润交易的共谋行为的标准。这些标准在筛选移动人群感知的潜在激励机制方面具有直接的实际效益。此外,我们还提出了可以抵抗任何形式的串通攻击的解决方案,甚至包括攻击者之间的利润交易。我们进行了大量的实验来验证我们的理论结果并评估我们提出的机制的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Insider Threat Detection Through Attributed Graph Clustering SEEAD: A Semantic-Based Approach for Automatic Binary Code De-obfuscation A Public Key Encryption Scheme for String Identification Vehicle Incident Hot Spots Identification: An Approach for Big Data Implementing Chain of Custody Requirements in Database Audit Records for Forensic Purposes
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1