Secure Grouping and Aggregation with MapReduce

International audienceMapReduce programming paradigm allows to process big data sets in parallel on a large cluster. We focus on a scenario where the data owner outsources her data on an honest-but-curious server. Our aim is to evaluate grouping and aggregation with SUM, COUNT, AVG, MIN, and MAX operations for an authorized user. For each of these five operations, we assume that the public cloud provider and the user do not collude i.e., the public cloud does not know the secret key of the user. We prove the security of our approach for each operation