Dynamic Accountable Storage: An Efficient Protocol for Real-time Cloud Storage Auditing

TL;DR

This paper introduces a dynamic, efficient cloud storage auditing protocol that supports insertions and deletions, improving upon previous static schemes by enabling real-time accountability and data recovery.

Contribution

We propose the IBLT tree data structure to enable dynamic, space-efficient auditing and data recovery in cloud storage protocols.

Findings

Supports insert and delete operations in cloud storage auditing

Enables efficient data recovery from lost or corrupted data

Improves practicality of accountable storage protocols

Abstract

Ateniese, Goodrich, Lekakis, Papamanthou, Paraskevas, and Tamassia introduced the Accountable Storage protocol, which is a way for a client to outsource their data to a cloud storage provider while allowing the client to periodically perform accountability challenges. An accountability challenge efficiently recovers any pieces of data the server has lost or corrupted, allowing the client to extract the original copies of the damaged or lost data objects. A severe limitation of the prior accountable storage scheme of Ateniese et al., however, is that it is not fully dynamic. That is, it does not allow a client to freely insert and delete data from the outsourced data set after initializing the protocol, giving the protocol limited practical use in the real world. In this paper, we present Dynamic Accountable Storage, which is an efficient way for a client to periodically audit their cloud storage while also supporting insert and delete operations on the data set. To do so, we introduce a data structure, the IBLT tree, which allows either the server or the client to reconstruct data the server has lost or corrupted in a space-efficient way.