SIA: Secure information aggregation in sensor networks

Abstract

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. *

Secure distributed top-k aggregation

“…the ordering, and hence top-k ranked data. Now, we extend the model to the case where the aggregator is untrusted, as is the case in the single aggregator model of Chan et al [15]. It is clear that if the aggregate is vulnerable to local data falsification by the data providers, then it is also vulnerable to manipulation by a corrupt aggregator.…”

“…Distributed aggregation protocols [1]- [7] are inherently vulnerable to stealthy data modification [14], [15] attacks, severely reducing their utility for critical applications. Extensive work has been carried out in the field of secure aggregation to assure the integrity of aggregates [15]- [20].…”

“…We consider an active stealthy insider adversary [15], which corrupts some fraction t ∈ [0, 1) of the node population. Corrupt nodes may attempt to modify either local observations or partial aggregates as well as dropping update messages, but attempt to do so while evading detection.…”

“…The problem becomes even harder when considering the cooperative processing in distributed aggregation systems, since powerful attacks against the data integrity can be carried out stealthily [15] by a small subset of corrupt nodes.…”

“…Previous approaches to secure distributed aggregation generally use expensive security protocols or place severe restrictions on the types of networks and services they support [15]- [20]. By contrast, we propose a simple, modular and low-overhead technique, using established principles of trusted systems [21], [22] to perform distributed aggregation in a secure fashion while preserving the scalability properties of the underlying aggregation protocol.…”