Query Privacy in Sensing-as-a-Service Platforms

  • Ruben Rios
  • David Nuñez
  • Javier Lopez
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 502)


The Internet of Things (IoT) promises to revolutionize the way we interact with the physical world. Even though this paradigm is still far from being completely realized, there already exist Sensing-as-a-Service (S\(^2\)aaS) platforms that allow users to query for IoT data. While this model offers tremendous benefits, it also entails increasingly challenging privacy issues. In this paper, we concentrate on the protection of user privacy when querying sensing devices through a semi-trusted S\(^2\)aaS platform. In particular, we build on techniques inspired by proxy re-encryption and k-anonymity to tackle two intertwined problems, namely query privacy and query confidentiality. The feasibility of our solution is validated both analytically and empirically.



This paper has been partially supported by the Junta de Andalucía through the project FISICCO (P11-TIC-07223) and the Spanish Ministry of Economy and Competitiveness through the PERSIST (TIN2013-41739-R) and SMOG (TIN2016-79095-C2-1-R) projects.


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Copyright information

© IFIP International Federation for Information Processing 2017

Authors and Affiliations

  1. 1.Network, Information and Computer Security (NICS) Lab, Computer Science DepartmentUniversity of MálagaMálagaSpain

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