Cryptology ePrint Archive: Report 2020/1501

PANCAKE: Frequency Smoothing for Encrypted Data Stores

Paul Grubbs and Anurag Khandelwal and Marie-Sarah Lacharité and Lloyd Brown and Lucy Li and Rachit Agarwal and Thomas Ristenpart

Abstract: We present PANCAKE, the first system to protect key-value stores from access pattern leakage attacks with small constant factor bandwidth overhead. PANCAKE uses a new approach, that we call frequency smoothing, to transform plaintext accesses into uniformly distributed encrypted accesses to an encrypted data store. We show that frequency smoothing prevents access pattern leakage attacks by passive persistent adversaries in a new formal security model. We integrate PANCAKE into three key-value stores used in production clusters, and demonstrate its practicality: on standard benchmarks, PANCAKE achieves 229× better throughput than non-recursive Path ORAM - within 3–6× of insecure baselines for these key-value stores.

Category / Keywords: cryptographic protocols / encrypted search

Original Publication (with major differences): Usenix Security 2020

Date: received 30 Nov 2020

Contact author: paulgrubbs12 at gmail com,anurag khandelwal@yale edu

Available format(s): PDF | BibTeX Citation

Version: 20201202:100338 (All versions of this report)

Short URL: ia.cr/2020/1501


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