Shroud: ensuring private access to large-scale data in the data center

TLDR

Online service providers face privacy risks from user data, and while encryption helps, access patterns still leak information; a virtual disk like Shroud can be applied to many applications and aims to conceal accesses across hundreds of terabytes. The authors introduce Shroud, a storage system that hides data access patterns from servers to protect user privacy. Shroud operates as a virtual disk that allows address‑oblivious block lookups, using adapted oblivious RAM algorithms and oblivious aggregation to parallelize across many inexpensive secure coprocessors, thereby hiding accesses over hundreds of terabytes and reducing latency. Evaluation on emulation and secure coprocessor implementation shows that the adaptations make private data access more practical.

Abstract

Recent events have shown online service providers the perils of possessing private information about users. Encrypting data mitigates but does not eliminate this threat: the pattern of data accesses still reveals information. Thus, we present Shroud, a general storage system that hides data access patterns from the servers running it, protecting user privacy. Shroud functions as a virtual disk with a new privacy guarantee: the user can look up a block without revealing the block's address. Such a virtual disk can be used for many purposes, including map lookup, microblog search, and social networking.Shroud aggressively targets hiding accesses among hundreds of terabytes of data. We achieve our goals by adapting oblivious RAM algorithms to enable large-scale parallelization. Specifically, we show, via new techniques such as oblivious aggregation, how to securely use many inexpensive secure coprocessors acting in parallel to improve request latency. Our evaluation combines large-scale emulation with an implementation on secure coprocessors and suggests that these adaptations bring private data access closer to practicality.