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A Framework for Privacy-Aware User Data Trading

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Part of the Lecture Notes in Computer Science book series (LNISA,volume 7899)

Abstract

Data about users is rapidly growing, collected by various online applications and databases. The ability to share user data across applications can offer benefits to user in terms of personalized services, but at the same time poses privacy risks of disclosure of personal information. Hence, there is a need to ensure protection of user privacy while enabling user data sharing for desired personalized services. We propose a policy framework for user data sharing based on the purpose of adaptation. The framework is based on the idea of a market, where applications can offer and negotiate user data sharing with other applications according to an explicit user-editable and negotiable privacy policy that defines the purpose, type of data, retention period and price.

Keywords

  • Privacy
  • Personalization
  • User Data Sharing
  • Policy
  • Incentives
  • Trust
  • Market
  • Framework

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Iyilade, J., Vassileva, J. (2013). A Framework for Privacy-Aware User Data Trading. In: Carberry, S., Weibelzahl, S., Micarelli, A., Semeraro, G. (eds) User Modeling, Adaptation, and Personalization. UMAP 2013. Lecture Notes in Computer Science, vol 7899. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38844-6_28

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  • DOI: https://doi.org/10.1007/978-3-642-38844-6_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38843-9

  • Online ISBN: 978-3-642-38844-6

  • eBook Packages: Computer ScienceComputer Science (R0)