Prism: Private Verifiable Set Computation over Multi-Owner Outsourced Databases
This addresses the need for secure and verifiable data computation in scenarios with multiple data owners, such as in collaborative analytics, but it is incremental as it builds on secret-sharing techniques.
The paper tackles the problem of computing private set operations and aggregates over multi-owner outsourced databases, proposing Prism, a secret sharing-based approach that achieves efficient implementation with at most two rounds of communication and supports result verification, scaling better than prior methods in terms of data owners and database sizes.
This paper proposes Prism, a secret sharing based approach to compute private set operations (i.e., intersection and union), as well as aggregates over outsourced databases belonging to multiple owners. Prism enables data owners to pre-load the data onto non-colluding servers and exploits the additive and multiplicative properties of secret-shares to compute the above-listed operations in (at most) two rounds of communication between the servers (storing the secret-shares) and the querier, resulting in a very efficient implementation. Also, Prism does not require communication among the servers and supports result verification techniques for each operation to detect malicious adversaries. Experimental results show that Prism scales both in terms of the number of data owners and database sizes, to which prior approaches do not scale.