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International Symposium on Privacy Enhancing Technologies Symposium

PETS 2010: Privacy Enhancing Technologies pp 273–290Cite as

How to Share Your Favourite Search Results while Preserving Privacy and Quality

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 6205))

Abstract

Personalised social search is a promising avenue to increase the relevance of search engine results by making use of recommendations made by friends in a social network. More generally a whole class of systems take user preferences, aggregate and process them, before providing a view of the result to others in a social network. Yet, those systems present privacy risks, and could be used by spammers to propagate their malicious preferences. We present a general framework to preserve privacy while maximizing the benefit of sharing information in a social network, as well as a concrete proposal making use of cohesive social group concepts from social network analysis. We show that privacy can be guaranteed in a k-anonymity manner, and disruption through spam is kept to a minimum in a real world social network.

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Author information

Authors and Affiliations

  1. Microsoft Research, One Microsoft Way, Redmond, WA, 98052, 6399, U.S.

    George Danezis, Shuo Chen & Emre Kıcıman

  2. Helsinki University of Technology, P.O. Box 5400, FI-02015, TKK, Finland

    Tuomas Aura

Authors
  1. George Danezis
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  2. Tuomas Aura
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  3. Shuo Chen
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  4. Emre Kıcıman
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Purdue University, 305 North University Street, IN 47907, 2107, West Lafayete, USA

    Mikhail J. Atallah

  2. Department of Computer Science & Engineering, University of Minnesota, MN 55455, Minneapolis, USA

    Nicholas J. Hopper

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Danezis, G., Aura, T., Chen, S., Kıcıman, E. (2010). How to Share Your Favourite Search Results while Preserving Privacy and Quality. In: Atallah, M.J., Hopper, N.J. (eds) Privacy Enhancing Technologies. PETS 2010. Lecture Notes in Computer Science, vol 6205. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14527-8_16

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  • DOI: https://doi.org/10.1007/978-3-642-14527-8_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14526-1

  • Online ISBN: 978-3-642-14527-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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