Paper Info
Title
DPDA: A Differentially Private Double Auction Scheme for Mobile Crowd Sensing.
Abstract
Mobile crowd sensing (MCS) takes advantage of pervasive mobile devices that are equipped with multi-sensors to collect rich data of a certain geographic area. Because of the importance of incentivizing users to participate, auction-based open MCS markets have been proposed in past literature. Note that their focus is to achieve critical economic properties but fail to protect bid privacy. Although there are limited schemes dealing with this issue, they are designed only for single-side auctions and are unsuitable for double-side auctions whose properties are quite different. In this paper, inspired by uniform pricing and exponential mechanism, we propose a differentially private double auction (DPDA) scheme for MCS to protect bid privacy for both auction sides. In addition, the traditional economic properties, such as gamma-truthfulness, individual rationality and budget balance, are guaranteed as well. Besides, we derive closed forms over the computation complexity and the approximate optimal platform revenue achieved by the scheme. Extensive simulations have been conducted on real-world datasets to validate the efficiency and effectiveness of DPDA.
Year
Venue
Field
2018
IEEE Conference on Communications and Network Security
Revenue,Rationality,Task analysis,Computer science,Deterministic pushdown automaton,Computer network,Mobile device,Common value auction,Double auction,Computation complexity
DocType
ISSN
Citations 
Conference
2474-025X
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Wenqiang Jin1115.61
Ming Li219420.48
Linke Guo324420.77
Lei Yang419437.52