Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/104491
Title: Differentially private mechanisms for budget limited mobile crowdsourcing
Authors: Han, Kai
Liu, Huan
Tang, Shaojie
Xiao, Mingjun
Luo, Jun
Keywords: Mobile Crowdsourcing
Differential Privacy
Engineering::Computer science and engineering
Issue Date: 2018
Source: Han, K., Liu, H., Tang, S., Xiao, M., & Luo, J. (2019). Differentially private mechanisms for budget limited mobile crowdsourcing. IEEE Transactions on Mobile Computing, 18(4), 934-946. doi:10.1109/TMC.2018.2848265
Series/Report no.: IEEE Transactions on Mobile Computing
Abstract: Recently, Mobile Crowdsourcing (MC) has aroused great interest on the part of both academic and industrial circles. One of the key problems in MC is designing the proper mechanisms to incentivize user participation, as users are typically self-interested and must consume a substantial amount of MC resources/costs. Although considerable research has been devoted to this problem, the majority of studies have neglected the privacy issue in mechanism design. In this study, we consider the scenario where a mobile crowdsourcing platform aims to maximize the crowdsourcing revenue under a budget constraint, and users are interested in maximizing their utility while keeping their cost private. We design differentially-private mechanisms for such a scenario under an offline setting where users bid their costs simultaneously and under an online setting where user bids are revealed one by one. We show that our mechanisms simultaneously achieve provable performance bounds with respect to several measures, including revenue, differential privacy, truthfulness, and individual rationality. Finally, we also conduct extensive numerical experiments to demonstrate the effectiveness of our approach.
URI: https://hdl.handle.net/10356/104491
http://hdl.handle.net/10220/50013
ISSN: 1536-1233
DOI: http://dx.doi.org/10.1109/TMC.2018.2848265
Rights: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TMC.2018.2848265
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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