Cloud computing is a boon for both business and private use, but data security concerns slow its adoption. Fully homomorphic encryption (FHE) offers the means by which cloud computing can be performed on encrypted data, obviating the data security concerns. FHE is not without its cost, as FHE operations take orders of magnitude more processing time and memory than the same operations on unencrypted data. Cloud computing can be leveraged to reduce the time taken by bringing to bear parallel processing. This thesis presents an implementatation of a processing dispatcher which takes an iterative set of operations on FHE encrypted data and splits them between a number of processing engines. A private cloud was implemented to support the processing engines. The processing time was measured with 1, 2, 4, and 8 processing engines, and an analysis of the time gained by parallel processing is presented.
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