Search for: All records

The SysteMPC workshop brings together cryptographers and systems researchers to discuss advances in overcom- ing practical challenges of using MPC in the wild. Topics of interest include cryptography and systems co-design, pro- gramming abstractions, modularity of cryptographic soft- ware, hardware acceleration, experimentation, and integra- tion with the existing ecosystem. In this short report, we summarize the inaugural edition of the workshop, which was held on July 10, 2025 at Boston University. 

We present Apache Flink 2.0, an evolution of the popular stream processing system's architecture that decouples computation from state management. Flink 2.0 relies on a remote distributed file system (DFS) for primary state storage and uses local disks as a secondary cache, with state updates streamed continuously and directly to the DFS. To address the latency implications of remote storage, Flink 2.0 incorporates an asynchronous runtime execution model. Furthermore, Flink 2.0 introduces ForSt, a novel state store featuring a unified file system that enables faster and lightweight checkpointing, recovery, and reconfiguration with minimal intrusion to the existing Flink runtime architecture. Using a comprehensive set of Nexmark benchmarks and a large-scale stateful production workload, we evaluate Flink 2.0's large-state processing, checkpointing, and recovery mechanisms. Our results show significant performance improvements and reduced resource utilization compared to the baseline Flink 1.20 implementation. Specifically, we observe up to 94% reduction in checkpoint duration, up to 49× faster recovery after failures or a rescaling operation, and up to 50% cost savings. 

We present Secrecy, a system for privacy-preserving collaborative analytics as a service. Secrecy allows multiple data holders to contribute their data towards a joint analysis in the cloud, while keeping the data siloed even from the cloud providers. At the same time, it enables cloud providers to offer their services to clients who would have otherwise refused to perform a computation altogether or insisted that it be done on private infrastructure. Secrecy ensures no information leakage and provides provable security guarantees by employing cryptographically secure Multi-Party Computation (MPC). In Secrecy we take a novel approach to optimizing MPC execution by co-designing multiple layers of the system stack and exposing the MPC costs to the query engine. To achieve practical performance, Secrecy applies physical optimizations that amortize the inherent MPC overheads along with logical optimizations that dramatically reduce the computation, communication, and space requirements during query execution. Our multi-cloud experiments demonstrate that Secrecy improves query performance by over 1000x compared to existing approaches and computes complex analytics on millions of data records with modest use of resources.