Limiting the Influence of Low Quality Information in Community Sensing

We consider a community of private sensors that collect measurements of a physical phenomenon, such as air pollution, and report it to a center. The center should be able to prevent low quality reports from degrading the quality of the aggregated information, as there are numerous reasons for operators to inject false sensor data. Hence, it is necessary to track the quality of the sensors over time in order to filter out low quality and malicious reports. To achieve this, we construct a reputation system with a guaranteed bounds on negative impact that malicious sensors can cause, and we evaluate its performance on a realistic dataset.