Observing and preventing leakage in MapReduce

Abstract

The use of public cloud infrastructure for storing and processing large datasets raises new security concerns. Current solutions propose encrypting all data, and accessing it in plaintext only within secure hardware. Nonetheless, the distributed processing of large amounts of data still involves intensive encrypted communications between different processing and network storage units, and those communications patterns may leak sensitive information. We consider secure implementation of MapReduce jobs, and analyze their intermediate traffic between mappers and reducers. Using datasets that include personal and geographical data, we show how an adversary that observes the runs of typical jobs ..