Privacy-preserving public auditing with data deduplication in cloud computing

Naelah Abdulrahman Alkhojandi

doi:10.32920/ryerson.14668344

Abstract

Storage represents one of the most commonly used cloud services. Data integrity and storage efficiency are two key requirements when storing users’ data. Public auditability, where users can employ a Third Part Auditor (TPA) to ensure data integrity, and efficient data deduplication which can be used to eliminate duplicate data and their corresponding authentication tags before sending the data to the cloud, offer possible solutions to address these requirements. In this thesis, we propose a privacy preserving public auditing scheme with data deduplication. We also present an extension of our proposed scheme that enables the TPA to perform multiple auditing tasks at the same time. Our analytical and experimental results show the efficiency of the batch auditing by reducing the number of pairing operations need for the auditing. Then, we extend our work to support user revocation where one of the users wants to leave the enterprise.

Highlights

One of the most important services in cloud computing is data storage, which allows users to store their data in the cloud
We have to provide proofs that the cloud server can only compute the correct reply to the Third Part Auditor (TPA) inquiry if the integrity of the data stored on the cloud is preserved
To verify the integrity of the data stored in the cloud considering the large size of that data and the limited computing resources of users, it is important to enable public auditing services which is the focus of this thesis

Summary

Introduction

One of the most important services in cloud computing is data storage, which allows users to store their data in the cloud. To verify the integrity of data stored in the cloud and to save computational resources of cloud users, it is important to enable auditing services, including those done on behalf of users by the TPA that can check the integrity of their data(Wang et al(2013a)Wang, Chow, Wang, Ren, and Lou). We use the results from (Wang et al(2013a)Wang, Chow, Wang, Ren, and Lou) and (Boldyreva(2003)) to propose a privacy-preserving public auditing protocol, which enables cross-user data deduplication achieving both data integrity and storage efficiency. Thesis Outline: The rest of this chapter provides a brief introduction of cloud computing including its definition, characteristics, service models, deployment models, and security issues. It provides an overview of the concept of data deduplication technique including definition, ratio, benefits, and types. We explain some notations and preliminaries which are used in some of the literature and the proposed scheme

Methods

Results

Conclusion