Sybil-Proof Online Incentive Mechanisms for Crowdsensing

Jian Lin, Ming Li, Dejun Yang, Guoliang Xue

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

Crowdsensing leverages the rapid growth of sensor-embedded smartphones and human mobility for pervasive information collection. To incentivize smartphone users to participate in crowdsensing, many auction-based incentive mechanisms have been proposed for both offline and online scenarios. It has been demonstrated that the Sybil attack may undermine these mechanisms. In a Sybil attack, a user illegitimately pretends multiple identities to gain benefits. Sybil-proof incentive mechanisms have been proposed for the offline scenario. However, the problem of designing Sybil-proof online incentive mechanisms for crowdsensing is still open. Compared to the offline scenario, the online scenario provides users one more dimension of flexibility, i.e., active time, to conduct Sybil attacks, which makes this problem more challenging. In this paper, we design Sybil-proof online incentive mechanisms to deter the Sybil attack for crowdsensing. Depending on users' flexibility on performing their tasks, we investigate both single-minded and multi-minded cases and propose SOS and SOM, respectively. SOS achieves computational efficiency, individual rationality, truthfulness, and Sybil-proofness. SOM achieves individual rationality, truthfulness, and Sybil-proofness. Through extensive simulations, we evaluate the performance of SOS and SOM.

Original languageEnglish (US)
Title of host publicationINFOCOM 2018 - IEEE Conference on Computer Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2438-2446
Number of pages9
Volume2018-April
ISBN (Electronic)9781538641286
DOIs
StatePublished - Oct 8 2018
Event2018 IEEE Conference on Computer Communications, INFOCOM 2018 - Honolulu, United States
Duration: Apr 15 2018Apr 19 2018

Other

Other2018 IEEE Conference on Computer Communications, INFOCOM 2018
CountryUnited States
CityHonolulu
Period4/15/184/19/18

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Sybil-Proof Online Incentive Mechanisms for Crowdsensing'. Together they form a unique fingerprint.

  • Cite this

    Lin, J., Li, M., Yang, D., & Xue, G. (2018). Sybil-Proof Online Incentive Mechanisms for Crowdsensing. In INFOCOM 2018 - IEEE Conference on Computer Communications (Vol. 2018-April, pp. 2438-2446). [8486418] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INFOCOM.2018.8486418