Repeatable Oblivious Shuffling of Large Outsourced Data Blocks

As data outsourcing becomes popular, oblivious algorithms have raised extensive attentions. Their control flow and data access pattern appear to be independent of the input data they compute on. Oblivious algorithms, therefore, are especially suitable for secure processing in outsourced environments. In this work, we focus on oblivious shuffling algorithms that aim to shuffle encrypted data blocks outsourced to a cloud server without disclosing the actual permutation of blocks to the server. Existing oblivious shuffling algorithms suffer from issues of heavy communication cost and client computation cost for shuffling large-sized blocks because all outsourced blocks must be downloaded to the client for shuffling or peeling off extra encryption layers. To help eliminate this void, we introduce the "repeatable oblivious shuffling" notation that avoids moving blocks to the client and thus restricts the communication and client computation costs to be independent of the block size. For the first time, we present a concrete construction of repeatable oblivious shuffling using additively homomorphic encryption. The comprehensive evaluation of our construction shows its effective usability in practice for shuffling large-sized blocks.