A Differentially Private Auction Mechanism in Online Social Networks

Hu, X; Ye, D; Zhu, T; Huo, H

A Differentially Private Auction Mechanism in Online Social Networks

Hu, X Ye, D

Zhu, T

Huo, H

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Publisher:: Springer
Publication Type:: Journal Article
Citation:: Journal of Systems Science and Systems Engineering, 2021, 30, (4), pp. 386-399
Issue Date:: 2021-08-01

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Field	Value	Language
dc.contributor.author	Hu, X
dc.contributor.author	Ye, D https://orcid.org/0000-0002-7561-0992
dc.contributor.author	Zhu, T https://orcid.org/0000-0003-3411-7947
dc.contributor.author	Huo, H https://orcid.org/0000-0003-2440-714X
dc.date.accessioned	2022-06-21T01:28:37Z
dc.date.available	2022-06-21T01:28:37Z
dc.date.issued	2021-08-01
dc.identifier.citation	Journal of Systems Science and Systems Engineering, 2021, 30, (4), pp. 386-399
dc.identifier.issn	1004-3756
dc.identifier.issn	1861-9576
dc.identifier.uri	http://hdl.handle.net/10453/158292
dc.description.abstract	The growing popularity of users in online social network gives a big opportunity for online auction. The famous Information Diffusion Mechanism (IDM) is an excellent method even meet the incentive compatibility and individual rationality. Although the existing auction in online social network has considered the buyers’ information which is not known by the seller, current mechanism still can not preserve the privacy information of users in online social network. In this paper, we propose a novel mechanism based on the IDM and differential privacy. Our mechanism can successfully process the auction and at the same time preserve clients’ price information from neighbours. We achieved these by adding virtual nodes to each node and Laplace noise for its price in the auction process. We also formulate this mechanism on the real network and the random network, scale-free network to show the feasibility and effectiveness of the proposed mechanism. The evaluation shows that the result of our methods only depend on the noise added to the agents. It is independent from the agents’ original price.
dc.language	en
dc.publisher	Springer
dc.relation.ispartof	Journal of Systems Science and Systems Engineering
dc.relation.isbasedon	10.1007/s11518-021-5493-5
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	01 Mathematical Sciences, 08 Information and Computing Sciences, 09 Engineering
dc.subject.classification	Operations Research
dc.title	A Differentially Private Auction Mechanism in Online Social Networks
dc.type	Journal Article
utslib.citation.volume	30
utslib.for	01 Mathematical Sciences
utslib.for	08 Information and Computing Sciences
utslib.for	09 Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-06-21T01:28:36Z
pubs.issue	4
pubs.publication-status	Published
pubs.volume	30
utslib.citation.issue	4

Abstract:

The growing popularity of users in online social network gives a big opportunity for online auction. The famous Information Diffusion Mechanism (IDM) is an excellent method even meet the incentive compatibility and individual rationality. Although the existing auction in online social network has considered the buyers’ information which is not known by the seller, current mechanism still can not preserve the privacy information of users in online social network. In this paper, we propose a novel mechanism based on the IDM and differential privacy. Our mechanism can successfully process the auction and at the same time preserve clients’ price information from neighbours. We achieved these by adding virtual nodes to each node and Laplace noise for its price in the auction process. We also formulate this mechanism on the real network and the random network, scale-free network to show the feasibility and effectiveness of the proposed mechanism. The evaluation shows that the result of our methods only depend on the noise added to the agents. It is independent from the agents’ original price.

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http://hdl.handle.net/10453/158292