Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Privacy in Social Collective Intelligence Systems
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap.ORCID-id: 0000-0002-6938-4466
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap.
2014 (engelsk)Inngår i: Social Collective Intelligence: Combining the Powers of Humans and Machines to Build a Smarter Society / [ed] Miorandi, D., Maltese, V., Rovatsos, M., Nijholt, A., Stewart, J., Switzerland: Springer, 2014, 1, s. 105-124Kapittel i bok, del av antologi (Fagfellevurdert)
Abstract [en]

The impact of Social Collective Intelligent Systems (SCIS) on the individual right of privacy is discussed in this chapter under the light of the relevant privacy principles of the European Data Protection Legal Framework and the Organization for Economic Co-operation and Development (OECD) Privacy Guidelines. This chapter analyzes the impact and limits of profiling, provenance and reputation on the right of privacy and review the legal privacy protection for profiles. From the technical perspective, we discuss opportunities and challenges for designing privacy-preserving systems for SCIS concerning collectives and decentralized systems. Furthermore, we present a selection of privacy-enhancing technologies that are relevant for SCIS: anonymous credentials, transparency-enhancing tools and the PrimeLife Policy Language. Finally, we discuss how these technologies can help to enforce the main legal principles of the European Data Protection Legal Framework, and argue how provenance and reputation can be designed in a privacy preserving manner.

sted, utgiver, år, opplag, sider
Switzerland: Springer, 2014, 1. s. 105-124
Serie
Computational Social Sciences Series
Emneord [en]
privacy, collective, profiling, legal, anonymity, transparency
HSV kategori
Forskningsprogram
Datavetenskap
Identifikatorer
URN: urn:nbn:se:kau:diva-38146ISBN: 978-3-319-08680-4 (tryckt)OAI: oai:DiVA.org:kau-38146DiVA, id: diva2:859936
Tilgjengelig fra: 2015-10-09 Laget: 2015-10-09 Sist oppdatert: 2018-06-04bibliografisk kontrollert

Open Access i DiVA

fulltext(244 kB)71 nedlastinger
Filinformasjon
Fil FULLTEXT01.pdfFilstørrelse 244 kBChecksum SHA-512
46f0f5fca8c22549f82695dafb39529450db7a902960325009375cd60014e75793cf720496b35c834ca2d4d9b5fa65d55c7b15b9e563854e0d9a763c48abe478
Type fulltextMimetype application/pdf

Andre lenker

http://www.springer.com/gp/book/9783319086804

Søk i DiVA

Av forfatter/redaktør
Fischer-Hübner, SimoneMartucci, Leonardo A.
Av organisasjonen

Søk utenfor DiVA

GoogleGoogle Scholar
Totalt: 71 nedlastinger
Antall nedlastinger er summen av alle nedlastinger av alle fulltekster. Det kan for eksempel være tidligere versjoner som er ikke lenger tilgjengelige

isbn
urn-nbn

Altmetric

isbn
urn-nbn
Totalt: 264 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf