Opaque: An Oblivious and Encrypted Distributed Analytics Platform

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Authors: 

Wenting Zheng, Ankur Dave, Jethro G. Beekman, Raluca Ada Popa, Joseph E. Gonzalez, and Ion Stoica, University of California, Berkeley

Abstract: 

Many systems run rich analytics on sensitive data in the cloud, but are prone to data breaches. Hardware enclaves promise data confidentiality and secure execution of arbitrary computation, yet still suffer from access pattern leakage. We propose Opaque, a distributed data analytics platform supporting a wide range of queries while providing strong security guarantees. Opaque introduces new distributed oblivious relational operators that hide access patterns, and new query planning techniques to optimize these new operators. Opaque is implemented on Spark SQL with few changes to the underlying system. Opaque provides data encryption, authentication and computation verification with a performance ranging from 52% faster to 3.3x slower as compared to vanilla Spark SQL; obliviousness comes with a 1.6–46x overhead. Opaque provides an improvement of three orders of magnitude over state-of-the-art oblivious protocols, and our query optimization techniques improve performance by 2–5x.

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BibTeX
@inproceedings {201554,
author = {Wenting Zheng and Ankur Dave and Jethro G. Beekman and Raluca Ada Popa and Joseph E. Gonzalez and Ion Stoica},
title = {Opaque: An Oblivious and Encrypted Distributed Analytics Platform},
booktitle = {14th {USENIX} Symposium on Networked Systems Design and Implementation ({NSDI} 17)},
year = {2017},
isbn = {978-1-931971-37-9},
address = {Boston, MA},
pages = {283--298},
url = {https://www.usenix.org/conference/nsdi17/technical-sessions/presentation/zheng},
publisher = {{USENIX} Association},
month = mar,
}

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