posted on 2003-01-01, 00:00authored byBartosz Przydatek, Dawn Song, Adrian Perrig
Sensor networks promise viable solutions to many monitoring problems. However, the practical deployment of sensor networks faces
many challenges imposed by real-world demands. Sensor nodes
often have limited computation and communication resources and
battery power. Moreover, in many applications sensors are deployed in open environments, and hence are vulnerable to physical
attacks, potentially compromising the sensor’s cryptographic keys.
One of the basic and indispensable functionalities of sensor networks is the ability to answer queries over the data acquired by the
sensors. The resource constraints and security issues make designing mechanisms for information aggregation in large sensor networks particularly challenging.
In this paper, we propose a novel framework for secure information aggregation in large sensor networks. In our framework certain
nodes in the sensor network, called aggregators, help aggregating
information requested by a query, which substantially reduces the
communication overhead. By constructing efficient random sampling mechanisms and interactive proofs, we enable the user 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 the average of
the measurements, for the estimation of the network size, and for
finding the minimum and maximum sensor reading. Our protocols
require only sublinear communication between the aggregator and
the user. To the best of our knowledge, this paper is the first on
secure information aggregation in sensor networks that can handle
a malicious aggregator and sensor nodes.