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Ontology-Enabled Access Control and Privacy Recommendations

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Mining, Modeling, and Recommending 'Things' in Social Media (MUSE 2013, MSM 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8940))

Abstract

Recent trends in ubiquitous computing target to provide user-controlled servers, providing a single point of access for managing different personal data in different Online Social Networks (OSNs), i.e. profile data and resources from various social interaction services (e.g., LinkedIn, Facebook, etc.). Ideally, personal data should remain independent of the environment, e.g., in order to support flexible migration to new landscapes. Such information interoperability can be achieved by ontology-based information representation and management. In this paper we present achievements and experiences of the di.me project, with respect to access control and privacy preservation in such systems. Special focus is put on privacy issues related to linkability and unwanted information disclosure. These issues could arise for instance when collecting and integrating information of different social contacts and their live streams (e.g., activity status, live posts, etc.). Our approach provides privacy recommendations by leveraging (1) the detection of semantic equivalence between contacts as portrayed in online profiles and (2) NLP techniques for analysing shared live streams. The final results after 3 years are presented and the portability to other environments is shortly discussed.

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Notes

  1. 1.

    http://www.dime-project.eu/.

  2. 2.

    https://github.com/dime-project/meta.

  3. 3.

    The system calculates trust values based on the privacy of exchanged content and its distribution, or can be set manually. For more information see e.g. [6] and [7].

  4. 4.

    As in cases of many alpha releases it is almost impossible to get reliable results for an evaluation, we restricted the set of systems for this analysis to the following five stable system implementations: Diaspora, Friendica, Jappix, Kune and StatusNet.

  5. 5.

    The project implemented a user-driven design process and requirements were refined several studies and validations.

  6. 6.

    Cf. http://www.dime-project.eu for details on the consortium application partners.

  7. 7.

    Also in terms of innovation!.

  8. 8.

    http://www.oscaf.org/.

  9. 9.

    http://www.semanticdesktop.org/ontologies/2007/11/01/pimo/.

  10. 10.

    http://www.semanticdesktop.org/ontologies/2009/11/08/nso/.

  11. 11.

    http://www.semanticdesktop.org/ontologies/2007/08/15/nao/.

  12. 12.

    http://www.semanticdesktop.org/ontologies/2011/10/05/dao/.

  13. 13.

    http://www.semanticdesktop.org/ontologies/nao/.

  14. 14.

    http://www.semanticdesktop.org/ontologies/2007/03/22/nco/.

  15. 15.

    http://www.w3.org/RDF/.

  16. 16.

    http://lod-cloud.net/.

  17. 17.

    http://wiki.dbpedia.org/OnlineAccess.

  18. 18.

    http://www.semanticdesktop.org/ontologies/2011/10/05/dlpo/.

  19. 19.

    Although an authoritative scientific evaluation is still forthcoming, preliminary experiments suggest the following indicative F-measures: Persons: 51 %, Locations: 60 %, Events: 45 %.

  20. 20.

    http://vimeo.com/dimeproject/videos.

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Author information

Authors and Affiliations

  1. Department Business Information Systems IV, University of Regensburg, Regensburg, Germany

    Marcel Heupel

  2. Research Group IT Security Management, University of Siegen, Siegen, Germany

    Lars Fischer

  3. MT AG, Ratingen, Germany

    Mohamed Bourimi

  4. Organized Knowledge Group, Fraunhofer IAIS, Bonn, Germany

    Simon Scerri

Authors
  1. Marcel Heupel
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  2. Lars Fischer
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  3. Mohamed Bourimi
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  4. Simon Scerri
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Corresponding author

Correspondence to Marcel Heupel .

Editor information

Editors and Affiliations

  1. University of Kassel, Kassel, Germany

    Martin Atzmueller

  2. Microsoft, Beijing, China

    Alvin Chin

  3. University of Kassel, Kassel, Germany

    Christoph Scholz

  4. Norwegian University of Science and Technology, Trondheim, Norway

    Christoph Trattner

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Heupel, M., Fischer, L., Bourimi, M., Scerri, S. (2015). Ontology-Enabled Access Control and Privacy Recommendations. In: Atzmueller, M., Chin, A., Scholz, C., Trattner, C. (eds) Mining, Modeling, and Recommending 'Things' in Social Media. MUSE MSM 2013 2013. Lecture Notes in Computer Science(), vol 8940. Springer, Cham. https://doi.org/10.1007/978-3-319-14723-9_3

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  • DOI: https://doi.org/10.1007/978-3-319-14723-9_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14722-2

  • Online ISBN: 978-3-319-14723-9

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