@conference {300591,
	title = {Shroud: Ensuring Private Access to Large-Scale Data in the Data Center},
	booktitle = {FAST},
	year = {2013},
	address = {San Jose, CA},
	abstract = {Recent events have shown online service providers\&nbsp;the perils of possessing private information about users.\&nbsp;Encrypting data mitigates but does not eliminate this\&nbsp;threat: the pattern of data accesses still reveals information.\&nbsp;Thus, we present Shroud, a general storage system\&nbsp;that hides data access patterns from the servers running\&nbsp;it, protecting user privacy. Shroud functions as a virtual\&nbsp;disk with a new privacy guarantee: the user can look up a\&nbsp;block without revealing the block{\textquoteright}s address. Such a virtual\&nbsp;disk can be used for many purposes, including map\&nbsp;lookup, microblog search, and social networking.

Shroud aggressively targets hiding accesses among\&nbsp;hundreds of terabytes of data. We achieve our goals by\&nbsp;adapting oblivious RAM algorithms to enable large-scale\&nbsp;parallelization. Specifically, we show, via new techniques\&nbsp;such as oblivious aggregation, how to securely\&nbsp;use many inexpensive secure coprocessors acting in parallel\&nbsp;to improve request latency. Our evaluation combines\&nbsp;large-scale emulation with an implementation on\&nbsp;secure coprocessors and suggests that these adaptations\&nbsp;bring private data access closer to practicality.},
	url = {http://scholar.harvard.edu/files/mickens/files/shroud.pdf},
	author = {Jacob R. Lorch and Bryan Parno and James Mickens and Mariana Raykova and Joshua Schiffman}
}
