Processing sensitive data, such as those produced by body sensors, on
third-party untrusted clouds is particularly challenging without compromising
the privacy of the users generating it. Typically, these sensors generate large
quantities of continuous data in a streaming fashion. Such vast amount of data
must be processed efficiently and securely, even under strong adversarial
models. The recent introduction in the mass-market of consumer-grade processors
with Trusted Execution Environments (TEEs), such as Intel SGX, paves the way to
implement solutions that overcome less flexible approaches, such as those atop
homomorphic encryption. We present a secure streaming processing system built
on top of Intel SGX to showcase the viability of this approach with a system
specifically fitted for medical data. We design and fully implement a prototype
system that we evaluate with several realistic datasets. Our experimental
results show that the proposed system achieves modest overhead compared to
vanilla Spark while offering additional protection guarantees under powerful
attackers and threat models.Comment: 19th International Conference on Distributed Applications and
Interoperable System