  Cloud computing has made it possible for a user to be able to select a
computing service precisely when needed. However, certain factors such as
security of data and regulatory issues will impact a user's choice of using
such a service. A solution to these problems is the use of a hybrid cloud that
combines a user's local computing capabilities (for mission- or
organization-critical tasks) with a public cloud (for less influential tasks).
We foresee three challenges that must be overcome before the adoption of a
hybrid cloud approach: 1) data design: How to partition relations in a hybrid
cloud? The solution to this problem must account for the sensitivity of
attributes in a relation as well as the workload of a user; 2) data security:
How to protect a user's data in a public cloud with encryption while enabling
query processing over this encrypted data? and 3) query processing: How to
execute queries efficiently over both, encrypted and unencrypted data? This
paper addresses these challenges and incorporates their solutions into an
add-on tool for a Hadoop and Hive based cloud computing infrastructure.

Distributed, Parallel, and Cluster Computing