  Regulated industries, such as Healthcare and Finance, are starting to move
parts of their data and workloads to the public cloud. However, they are still
reluctant to trust the public cloud with their most sensitive records, and
hence leave them in their premises, leveraging the hybrid cloud architecture.
We address the security and performance challenges of big data analytics using
a hybrid cloud in a real-life use case from a hospital. In this use case, the
hospital collects sensitive patient data and wants to run analytics on it in
order to lower antibiotics resistance, a significant challenge in healthcare.
We show that it is possible to run large-scale analytics on data that is
securely stored in the public cloud encrypted using Apache Parquet Modular
Encryption (PME), without significant performance losses even if the secret
encryption keys are stored on-premises. PME is a standard mechanism for data
encryption and key management, not specific to any public cloud, and therefore
helps prevent vendor lock-in. It also provides privacy and integrity
guarantees, and enables granular access control to the data. We also present an
innovation in PME for lowering the performance hit incurred by calls to the Key
Management Service. Our solution therefore enables protecting large amounts of
sensitive data in hybrid clouds and still allows to efficiently gain valuable
insights from it.
