  Data splitting preserves privacy by partitioning data into various fragments
to be stored remotely and shared. It supports most data operations because data
can be stored in clear as opposed to methods that rely on cryptography.
However, majority of existing data splitting techniques do not consider data
already in the multi-cloud. This leads to unnecessary use of resources to
re-split data into fragments. This work proposes a data splitting framework
that leverages on existing data in the multi-cloud. It improves data splitting
mechanisms by reducing the number of splitting operations and resulting
fragments. Therefore, decreasing the number of storage locations a data owner
manages. Broadcasts queries locate third-party data fragments to avoid costly
operations when splitting data. This work examines considerations for the use
of third-party fragments and application to existing data splitting techniques.
The proposed framework was also applied to an existing data splitting mechanism
to complement its capabilities.
