Abstract
Data integrity in cloud databases is a topic that has received a much of attention from the research community. However, existing solutions mainly focus on the cloud providers that store data in relational databases, whereas nowadays many cloud providers store data in non-relational databases as well. In this paper, we focus on the particular family of non-relational databases—column-oriented stores, and present a protocol that will allow cloud users to verify the integrity of their data that resides on cloud databases of this type. We like our solution to be easily integrated with the existing real-world systems and therefore assume that we cannot modify the cloud; our protocol is implemented solely on the client side. We have implemented a prototype of our solution, that uses Cloud BigTable as a cloud database, and have evaluated its performance and correctness.
Highlights
For a long time, relational database management systems (RDBMS) have been the only solution for persistent data storage
The goal of this paper is to demonstrate that data integrity of column-oriented NoSQL databases in the cloud can be verified better than it was proposed in previous work
We focus on data integrity protection in the following two dimensions: 1. Correctness – Data received by the clients was originally uploaded to the cloud by the Data owner (DO) and has not been modified maliciously or mistakenly in the cloud side
Summary
Relational database management systems (RDBMS) have been the only solution for persistent data storage. Rather than store data in heavily structured tables, NoSQL systems prefer simpler data schema such as key-value pairs or collections of documents. NoSQL databases are usually classified into three groups, according to their data model: key-value stores, document-based stores, and column-oriented stores. The latter group was inspired by BigTable [3] - a distributed storage system developed by Google that is designed to manage very large amounts of structured data. – Development of a novel probabilistic method that allows users to verify data integrity of the data that resides in cloud column-oriented stores and its analysis.
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