Budget-Feasible Sybil-Proof Mechanisms for Crowdsensing

Xiang Liu, Weiwei Wu, Wanyuan Wang, Yuhang Xu, Xiumin Wang, Helei Cui

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

The rapid use of smartphones and devices leads to the development of crowdsensing (CS) systems where a large crowd of participants can take part in performing data collecting tasks in large-scale distributed networks. Participants/users in such systems are usually selfish and have private information, such as costs and identities. Budget-feasible mechanism design, as a sub-field of auction theory, is a useful paradigm for crowdsensing, which naturally formulates the procurement scenario with buyers’ budgets being considered and allows the users to bid their private costs. Although the bidding behavior is well-regulated, budget-feasible mechanisms are still vulnerable to the Sybil attack where users may generate multiple fake identities to manipulate the system. Thus, it is vital to provide Sybil-proof budget-feasible mechanisms for crowdsensing. In this paper, we design a budget-feasible incentive mechanism which can guarantee truthfulness and deter Sybil attack. We prove that the proposed mechanism achieves individual rationality, truthfulness, budget feasibility, and Sybil-proofness. Extensive simulation results further validate the efficiency of the proposed mechanism.

Original languageEnglish
Title of host publicationFrontiers of Algorithmic Wisdom - International Joint Conference, IJTCS-FAW 2022, Revised Selected Papers
EditorsMinming Li, Xiaoming Sun
PublisherSpringer Science and Business Media Deutschland GmbH
Pages269-288
Number of pages20
ISBN (Print)9783031207952
DOIs
StatePublished - 2022
EventInternational Joint Conference on Theoretical Computer Science-Frontier of Algorithmic Wisdom, IJTCS-FAW 2022 - Hong Kong, China
Duration: 15 Aug 202219 Aug 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13461 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Joint Conference on Theoretical Computer Science-Frontier of Algorithmic Wisdom, IJTCS-FAW 2022
Country/TerritoryChina
CityHong Kong
Period15/08/2219/08/22

Keywords

  • Auction
  • Budget feasibility
  • Crowdsensing
  • Mechanism design
  • Sybil-proofness

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