Optimizing Path ORAM for Cloud Storage Applications

TL;DR

This paper presents an optimized Path ORAM implementation for cloud storage, specifically Dropbox, introducing innovations like dynamic tree architecture and multi-client support to enhance security and performance.

Contribution

The paper introduces several novel optimizations to Path ORAM, including dynamic tree resizing, multi-block fetching, and multi-client capabilities, tailored for cloud storage applications.

Findings

77% throughput increase

60% reduction in tree size

Effective obfuscation of access patterns

Abstract

We live in a world where our personal data are both valuable and vulnerable to misappropriation through exploitation of security vulnerabilities in online services. For instance, Dropbox, a popular cloud storage tool, has certain security flaws that can be exploited to compromise a user's data, one of which being that a user's access pattern is unprotected. We have thus created an implementation of Path Oblivious RAM (Path ORAM) for Dropbox users to obfuscate path access information to patch this vulnerability. This implementation differs significantly from the standard usage of Path ORAM, in that we introduce several innovations, including a dynamically growing and shrinking tree architecture, multi-block fetching, block packing and the possibility for multi-client use. Our optimizations together produce about a 77% throughput increase and a 60% reduction in necessary tree size; these numbers vary with file size distribution.