SecQSA: Secure Sampling-Based Quantile Summary Aggregation in Wireless Sensor Networks

Wireless sensor networks are widely expected to play a key role in the emerging Internet of Things (IoT)-based smart cities in which a large number of resource-constrained sensor nodes collect data about our physical environment to assist intelligent decision making. Since blindly forwarding all the sensed data to the base station may quickly deplete sensor nodes' limited energy, secure data aggregation has been considered as a key functionality in wireless sensor networks that allow the base station to acquire important statistics about the sensed data. While many secure data aggregation schemes have been proposed in the literature, most of them target simple statistics such as Sum, Count, Min/Max, and Median. In contrast, a quantile summary allows a base station to extract the phi-quantile for any 0 < phi < 1 of all the sensor readings in the network and can provide a more accurate characterization of the data distribution. How to realize secure quantile summary aggregation in wireless sensor networks remains an open challenge. In this paper, we fill this void by first evaluating the impact of a range of attacks on quantile summary aggregation using simulation and then introduce a novel secure quantile summary aggregation protocol for wireless sensor networks. Detailed simulation studies confirm the efficacy and efficiency of the proposed protocol.