Oblivious coopetitive analytics using hardware enclaves

Coopetitive analytics refers to cooperation among competing parties to run queries over their joint data. Regulatory, business, and liability concerns prevent these organizations from sharing their sensitive data in plaintext. We propose Oblivious Coopetitive Queries (OCQ), an efficient, general framework for oblivious coopetitive analytics using hardware enclaves. OCQ builds on Opaque, a Spark-based framework for secure distributed analytics, to execute coopetitive queries using hardware enclaves in a decentralized manner. Its query planner chooses how and where to execute each relational operator to prevent data leakage through side channels such as memory access patterns, network traffic statistics, and cardinality, while minimizing overhead. We implemented OCQ as an extension to Apache Spark SQL. We find that OCQ is up to 9.9x faster than Opaque, a state-of-the-art secure analytics framework which outsources all data and computation to an enclave-enabled cloud; and is up to 219x faster than implementing analytics using AgMPC, a state-of-the-art secure multi-party computation framework.