Paper 2014/382

Privacy-Enhanced Participatory Sensing with Collusion Resistance and Data Aggregation

Felix Günther, Mark Manulis, and Andreas Peter

Abstract

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.

Metadata
Available format(s)
PDF
Category
Applications
Publication info
Published elsewhere. Major revision. 13th International Conference on Cryptology and Network Security (CANS 2014)
Keywords
privacyparticipatory sensingcollusion resistancedata aggregation
Contact author(s)
guenther @ cs tu-darmstadt de
History
2014-09-12: last of 2 revisions
2014-05-28: received
See all versions
Short URL
https://ia.cr/2014/382
License
Creative Commons Attribution
CC BY

BibTeX

@misc{cryptoeprint:2014/382,
      author = {Felix Günther and Mark Manulis and Andreas Peter},
      title = {Privacy-Enhanced Participatory Sensing with Collusion Resistance and Data Aggregation},
      howpublished = {Cryptology {ePrint} Archive, Paper 2014/382},
      year = {2014},
      url = {https://eprint.iacr.org/2014/382}
}
Note: In order to protect the privacy of readers, eprint.iacr.org does not use cookies or embedded third party content.