Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

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

Michael T. Goodrich, Ryuto Kitagawa, Vinesh Sridhar

TL;DR

A data structure, the IBLT tree, is introduced, which allows either the server or the client to reconstruct data the server has lost or corrupted in a space-efficient way.

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.

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

TL;DR

A data structure, the IBLT tree, is introduced, which allows either the server or the client to reconstruct data the server has lost or corrupted in a space-efficient way.

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.

Paper Structure

This paper contains 21 sections, 18 theorems, 5 equations, 1 figure.

Table of Contents

  1. Introduction
  2. Other Related Work
  3. Our Contributions
  4. Accountable Storage
  5. Invertible Bloom Lookup Tables
  6. Accountable Storage
  7. The Server's Simple Way to Thwart Accountable Storage
  8. IBLT Tree
  9. Overview
  10. IBLT Tree General Framework
  11. Protected Cartesian IBLT Tree
  12. Our Dynamic Accountable Storage Construction
  13. Model
  14. Construction
  15. Analysis
  16. ...and 6 more sections

Key Result

lemma thmcounterlemma

Let $\mathbf{T}$ be an IBLT constructed using $q$ hash functions that stores a set of size $\delta$ using at least $(q+1)\delta$ cells and $q$ hash functions, then Peel($\textbf{T}$) succeeds with probability $1-O(\delta^{-q})$.

Figures (1)

  • Figure 1: An IBLT trees for a set of 43 blocks and $\beta=1$, where each node contains an IBLT of all the blocks in its subtree. If we set $\beta = 6$ and require each leaf to store at least $\beta / 2$ blocks and at most $\beta$ blocks, then the blue nodes would be removed while the red nodes would become the new leaf nodes. If $\beta$ increases further, then the tree becomes more compressed.

Theorems & Definitions (29)

  • lemma thmcounterlemma: eppstein_whats_2011goodrich_invertible_2011
  • theorem thmcountertheorem
  • lemma thmcounterlemma
  • corollary thmcountercorollary
  • lemma thmcounterlemma
  • corollary thmcountercorollary
  • definition thmcounterdefinition: Dynamic $\delta$-AS scheme
  • definition thmcounterdefinition: Dynamic $\delta$-AS scheme correctness
  • theorem thmcountertheorem: Dynamic $\delta$-Accountable Storage
  • theorem thmcountertheorem
  • ...and 19 more