Differentially private aggregation of distributed time-series with transformation and encryption

Abstract

We propose the first differentially private aggregation algorithm for distributed time-series data that offers good practical utility without any trusted server. This addresses two important challenges in participatory data-mining applications where (i) individual users collect temporally correlated time-series data (such as location traces, web history… (More)
DOI: 10.1145/1807167.1807247

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