Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Random dictatorship for privacy-preserving social choice
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. Hamilton Institute, Maynooth University, Maynooth, Ireland. (Skövde Artificial Intelligence Lab)ORCID iD: 0000-0002-0368-8037
2019 (English)In: International Journal of Information Security, ISSN 1615-5262, E-ISSN 1615-5270, p. 1-9Article in journal (Refereed) Epub ahead of print
Abstract [en]

Social choice provides methods for collective decisions. They include methods for voting and for aggregating rankings. These methods are used in multiagent systems for similar purposes when decisions are to be made by agents. Votes and rankings are sensitive information. Because of that, privacy mechanisms are needed to avoid the disclosure of sensitive information. Cryptographic techniques can be applied in centralized environments to avoid the disclosure of sensitive information. A trusted third party can then compute the outcome. In distributed environments, we can use a secure multiparty computation approach for implementing a collective decision method. Other privacy models exist. Differential privacy and k-anonymity are two of them. They provide privacy guarantees that are complementary to multiparty computation approaches, and solutions that can be combined with the cryptographic ones, thus providing additional privacy guarantees, e.g., a differentially private multiparty computation model. In this paper, we propose the use of probabilistic social choice methods to achieve differential privacy. We use the method called random dictatorship and prove that under some circumstances differential privacy is satisfied and propose a variation that is always compliant with this privacy model. Our approach can be implemented using a centralized approach and also a decentralized approach. We briefly discuss these implementations.

Place, publisher, year, edition, pages
2019. p. 1-9
Keywords [en]
Privacy, Social choice, Probabilistic social choice, Differential privacy, Random dictatorship
National Category
Computer Sciences
Research subject
Interaction Lab (ILAB)
Identifiers
URN: urn:nbn:se:his:diva-17812DOI: 10.1007/s10207-019-00474-7ISI: 000490528400001Scopus ID: 2-s2.0-85074583629OAI: oai:DiVA.org:his-17812DiVA, id: diva2:1365814
Available from: 2019-10-25 Created: 2019-10-25 Last updated: 2019-11-18Bibliographically approved

Open Access in DiVA

fulltext(348 kB)16 downloads
File information
File name FULLTEXT01.pdfFile size 348 kBChecksum SHA-512
bfcf4034cbd254d44d55d8ef109c33106a6b68d15de3856c9d35fafff6a7a1cf3bc0fcbd8343fbf3acfa330cc3c9633dcf75bf552d1a9bbeab3d617afb69425c
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Torra, Vicenç
By organisation
School of InformaticsThe Informatics Research Centre
In the same journal
International Journal of Information Security
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 16 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 113 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf