Privacy-Enhanced Participatory Sensing with Collusion Resistance and Data Aggregation

  • Felix Günther
  • Mark Manulis
  • Andreas Peter
Conference paper

DOI: 10.1007/978-3-319-12280-9_21

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8813)
Cite this paper as:
Günther F., Manulis M., Peter A. (2014) Privacy-Enhanced Participatory Sensing with Collusion Resistance and Data Aggregation. In: Gritzalis D., Kiayias A., Askoxylakis I. (eds) Cryptology and Network Security. CANS 2014. Lecture Notes in Computer Science, vol 8813. Springer, Cham


Participatory sensing enables new paradigms and markets for information collection based on the ubiquitous availability of smartphones, but also introduces privacy challenges for participating users and their data. In this work, we review existing security models for privacy-preserving participatory sensing and propose several improvements that are both of theoretical and practical significance.

We first address an important drawback of prior work, namely the lack of consideration of collusion attacks that are highly relevant for such multi-user settings. We explain why existing security models are insufficient and why previous protocols become insecure in the presence of colluding parties. We remedy this problem by providing new security and privacy definitions that guarantee meaningful forms of collusion resistance. We propose new collusion-resistant participatory sensing protocols satisfying our definitions: a generic construction that uses anonymous identity-based encryption (IBE) and its practical instantiation based on the Boneh-Franklin IBE scheme.

We then extend the functionality of participatory sensing by adding the ability to perform aggregation on the data submitted by the users, without sacrificing their privacy. We realize this through an additively-homomorphic IBE scheme which in turn is constructed by slightly modifying the Boneh-Franklin IBE scheme. From a practical point of view, the resulting scheme is suitable for calculations with small sensor readings/values such as temperature measurements, noise levels, or prices, which is sufficient for many applications of participatory sensing.


Privacy participatory sensing collusion resistance data aggregation cryptographic models additively homomorphic identity-based encryption 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Felix Günther
    • 1
  • Mark Manulis
    • 2
  • Andreas Peter
    • 3
  1. 1.CryptoplexityTechnische Universität DarmstadtGermany
  2. 2.Surrey Centre for Cyber SecurityUniversity of SurreyUnited Kingdom
  3. 3.Distributed and Embedded Security GroupUniversity of TwenteThe Netherlands

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