Existing oblivious storage systems provide strong security by hiding access patterns, but do not scale to sustain high throughput as they rely on a central point of coordination. To overcome this scalability bottleneck, we present Snoopy, an object store that is both oblivious and scalable such that adding more machines increases system throughput. Snoopy contributes techniques tailored to the high-throughput regime to securely distribute and efficiently parallelize every system component without prohibitive coordination costs. These techniques enable Snoopy to scale similarly to a plaintext storage system. Snoopy achieves 13.7× higher throughput than Obladi, a state-of-the-art oblivious storage system. Specifically, Obladi reaches a throughput of 6.7K requests/s for two million 160-byte objects and cannot scale beyond a proxy and server machine. For the same data size, Snoopy uses 18 machines to scale to 92K requests/s with average latency under 500ms. This work will appear at SOSP '21 and is joint work with Vivian Fang, Ioannis Demertzis, Natacha Crooks, and Raluca Ada Popa.
Emma Dauterman is a third-year PhD student working with Raluca Ada Popa and Ion Stoica in the UC Berkeley RISELab. She is broadly interested in building secure systems using cryptography. Her work is supported by a Microsoft Ada Lovelace research fellowship and a NSF GRFP fellowship.
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