SIA: Secure information aggregation in sensor networks

  • Authors:

  • Haowen Chan;Adrian Perrig;Bartosz Przydatek;Dawn Song

  • Affiliations:

  • Carnegie Mellon University, USA;(Correspd. CIC 2110, 4720 Forbes Avenue, Pittsburgh, PA 15213. Tel.: +1 412 268 2242/ Fax: +1 412 268 6779/ E-mail: adrian@ece.cmu.edu) Carnegie Mellon University, USA;(Research done while this author was at Carnegie Mellon University) ETH Zurich, Switzerland;Carnegie Mellon University, USA

  • Venue:
  • Journal of Computer Security - Special Issue on Security of Ad-hoc and Sensor Networks
  • Year:
  • 2007

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Abstract

In sensor networks, data aggregation is a vital primitive enabling efficient data queries. An on-site aggregator device collects data from sensor nodes and produces a condensed summary which is forwarded to the off-site querier, thus reducing the communication cost of the query. Since the aggregator is on-site, it is vulnerable to physical compromise attacks. A compromised aggregator may report false aggregation results. Hence, it is essential that techniques are available to allow the querier to verify the integrity of the result returned by the aggregator node. We propose a novel framework for secure information aggregation in sensor networks. By constructing efficient random sampling mechanisms and interactive proofs, we enable the querier to verify that the answer given by the aggregator is a good approximation of the true value, even when the aggregator and a fraction of the sensor nodes are corrupted. In particular, we present efficient protocols for secure computation of the median and average of the measurements, for the estimation of the network size, for finding the minimum and maximum sensor reading, and for random sampling and leader election. Our protocols require only sublinear communication between the aggregator and the user.