Towards Practical Oblivious Join

Many individuals and companies choose the public cloud as their data and IT infrastructure platform. But remote accesses over the data inevitably bring the issue of trust. Despite strong encryption schemes, adversaries can still learn sensitive information from encrypted data by observing data access patterns. Oblivious RAMs (ORAMs) are proposed to protect against access pattern attacks. However, directly deploying ORAM constructions in an encrypted database brings large computational overhead. In this work, we focus on oblivious joins over a cloud database. Existing studies in the literature are restricted to either primary-foreign key joins or binary equi-joins. Our major contribution is to support general binary and multiway equi-joins. We integrate B-tree indices into ORAMs for each input table and retrieve blocks through the indices in join processing. The key points are to address the security issue (i.e., leaking the number of accesses to any index) in the extended existing solutions and bound the total number of block accesses. Our index nested-loop join algorithm can also support some types of band joins obliviously. The effectiveness and efficiency of our algorithms are demonstrated through extensive evaluations over real-world datasets. Our method shows orders of magnitude speedup for oblivious multiway equi-joins in comparison with baseline algorithms.