Balancing Smartness and Privacy for the Ambient Intelligence

  • Harold van Heerde
  • Nicolas Anciaux
  • Ling Feng
  • Peter M. G. Apers
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4272)


Ambient Intelligence (AmI) will introduce large privacy risks. Stored context histories are vulnerable for unauthorized disclosure, thus unlimited storing of privacy-sensitive context data is not desirable from the privacy viewpoint. However, high quality and quantity of data enable smartness for the AmI, while less and coarse data benefit privacy. This raises a very important problem to the AmI, that is, how to balance the smartness and privacy requirements in an ambient world. In this article, we propose to give to donors the control over the life cycle of their context data, so that users themselves can balance their needs and wishes in terms of smartness and privacy.


Context Data Ambient Intelligence Privacy Requirement Query Service Coarse Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Harold van Heerde
    • 1
  • Nicolas Anciaux
    • 2
  • Ling Feng
    • 1
  • Peter M. G. Apers
    • 1
  1. 1.Centre for Telematics and Information TechnologyUniversity of TwenteThe Netherlands
  2. 2.INRIAFrance

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