Private and resilient data aggregation

Sensors are commonly deployed in hostile environment, and consequently a number of research works have focused on data aggregation schemes designed to be tolerant to attacks on sensor nodes. In parallel, schemes ensuring the confidentiality of sensor data have been proposed to address the emerging privacy concerns. We note that resilience against tampering attacks requires access to the sensor node´s data, while in privacy-preserving systems this data must remain confidential. In this work, we aim to reconcile these two seemingly conflicting objectives. We present a novel private and resilient aggregation system, in which an aggregator combines the data collected from sensor nodes and forwards the resulting sum to an analyst. Our scheme protects the privacy of the users from both honest-but-curious aggregator and analyst, while enabling the filtering of fake data values using a Private Range Test protocol.