MiniCrypt: Reconciling Encryption and Compression for Big Data Stores.

Raluca Ada Popa Security, Systems

More and more applications and web services generate larger and larger amounts of confidential data, such as user and financial data. On one hand, these systems must use encryption to ensure confidentiality, while on the other hand, they want to use compression to reduce costs and increase performance. Unfortunately, encryption and compression are in tension, leading many existing systems to support one but not the other. We propose MiniCrypt,  the first big data keyvalue store that reconciles encryption and compression, without compromising performance.  At the core of MiniCrypt is an observation on data compressibility trends in key-value stores, which enables grouping key-value pairs in small key packs, together with a set of new distributed systems techniques for retrieving, updating,  merging and splitting encrypted packs while preserving consistency and performance. Our evaluation shows that MiniCrypt compresses data by as much as 4 times with respect to the vanilla key-value store, and can increase
the server’s throughput by up to an order of magnitude by fitting more data in main memory.

Published On:

Presented At/In: EuroSys 2017

Link: https://pdfs.semanticscholar.org/5aa9/0f7bc1a8282daf74a65aec86022d7ddbad9b.pdf

Authors: Wenting Zheng, Raluca Ada Popa, Ion Stoica, Rachit Agarwal, Frank Li