Secure cross-site analytics on OpenShift logs
The project aims to explore whether cryptographically secure Multi-Party Computation, or MPC for short, can be used to perform secure cross-site analytics on OpenShift logs with minimum client participation. MPC enables mutually distrusting parties (in our case Red Hat clients) to compute arbitrary functions (e.g., identifying common trends involving crashes or failures) over their collective private data (in our case log files) while keeping their data siloed from each other and from external adversaries. Contrary to traditional MPC approaches that require data owners to act as computing parties using private resources, we will focus on a setting where clients outsource certain queries on their logs to untrusted non-colluding entities (e.g., Red Hat and ORCI) while retaining the full security guarantees of MPC. The proposed research will build on prior and ongoing work by the PI and, in particular, on Secrecy, a novel MPC framework for secure outsourced analytics with no information leakage that we build at BU.
PI: John Liagouris
- Project repository: https://github.com/jliagouris/openshift-logs
- November 2022 Secure cross-site analytics on OpenShift logs” at the BU Systems Seminar (Speaker: Jingyu Su)