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Privacy in Social Collective Intelligence Systems

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Social Collective Intelligence

Part of the book series: Computational Social Sciences ((CSS))

Abstract

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 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 including anonymous credentials, transparency-enhancing tools and the PrimeLife Policy Language (PPL) and discuss how these technologies can help to enforce the main legal principles of the European Data Protection Legal Framework.

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Notes

  1. 1.

    The Article 29 Working Party consists of a representative from the data protection authority of each EU Member State, the European Data Protection Supervisor and the European Commission.

  2. 2.

    The Article 29 Working Party statement is close to the definition of anonymity from Pfitzmann and Hansen [37]: “anonymity of a subject from an attackers perspective means that the attacker cannot sufficiently identify the subject within a set of subjects, the anonymity set”, which is commonly used in the computer security and privacy area.

  3. 3.

    According to EU Data Protection Directive 95/46/EC, a data controller is defined as the entity that alone or jointly with others determines the purposes and means of personal data processing.

  4. 4.

    According to EU Data Protection Directive 95/46/EC, a data subject is a natural person about whom personal data are processed has in regard to his personal data.

  5. 5.

    Role pseudonyms are pseudonyms that are limited to a specific role or context [37].

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Authors and Affiliations

  1. Karlstad University, 651-88, Karlstad, Sweden

    Simone Fischer-Hübner & Leonardo A. Martucci

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  1. Simone Fischer-Hübner
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  2. Leonardo A. Martucci
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Correspondence to Leonardo A. Martucci .

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Editors and Affiliations

  1. CREATE-NET, Trento, Italy

    Daniele Miorandi

  2. University of Trento, Trento, Italy

    Vincenzo Maltese

  3. School of Informatics Informatics, The University of Edinburgh, Edinburgh, United Kingdom

    Michael Rovatsos

  4. Faculty EEMCS, University of Twente, Enschede, The Netherlands

    Anton Nijholt

  5. The University of Edinburgh, Edinburgh, United Kingdom

    James Stewart

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Fischer-Hübner, S., Martucci, L.A. (2014). Privacy in Social Collective Intelligence Systems. In: Miorandi, D., Maltese, V., Rovatsos, M., Nijholt, A., Stewart, J. (eds) Social Collective Intelligence. Computational Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-08681-1_6

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  • DOI: https://doi.org/10.1007/978-3-319-08681-1_6

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