Title: Stargazing in the Dark: Secure Skyline Queries with SGX
Authors: Jiafan Wang, Minxin Du and Sherman S. M. Chow
Abstract: Skylining for multi-criteria decision making is widely applicable and often involves sensitive data that should be encrypted, especially when the database and query engine are outsourced to an untrusted cloud platform. The state-of-the-art designs (ICDE'17) of skylining over encrypted data, while relying on two non-colluding servers, are still slow ? taking around three hours to get the skyline for 9000 2-D points. This paper proposes a very efficient solution with a trusted processor such as SGX. A challenge is to support dynamic queries while keeping the memory footprint small and simultaneously preventing unintended leakage with only lightweight cryptographic primitives. Our proposed approach iteratively loads data to the memory-limited SGX on-demand and builds a binary-tree-like index for logarithmic query time. For millions of points, we gain 6000 - 28000x improvement in query time(ICDE'17)
