Data Access Management System in Azure Blob Storage and AWS S3 Multi-Cloud Storage Environments

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Author(s): Yaser Mansouri (Adelaide University, Australia)and Rajkumar Buyya (The University of Melbourne, Australia)
Copyright: 2020
Pages: 18
Source title: Handbook of Research on Intrusion Detection Systems
Source Author(s)/Editor(s): Brij B. Gupta (National Institute of Technology, Kurukshetra, India)and Srivathsan Srinivasagopalan (AT&T, USA)
DOI: 10.4018/978-1-7998-2242-4.ch007

Keywords: Cyber and Network Security / Information Science Reference / Information Security & Privacy / Security & Forensics

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Abstract

Multi-cloud storage offers better Quality of Service (QoS) such as availability, durability, and users' perceived latency. The exploitation of price differences across cloud-based storage services is a motivate example of storing data in different Geo-graphically data stores, where data migration is also a choice to achieve more cost optimization. However, this requires migrating data in tolerable time from the perspective of users. This chapter first proposes a comprehensive review on different classes of data stores inspiring data migration within and across data stores. Then, it presents the design of a system prototype spanned across storage services of Amazon Web Services (AWS) and Microsoft Azure employing their RESTful APIs to store, retrieve, delete, and migrate data. Finally, the experimental results show that the data migration can be conducted in a few seconds for data with a magnitude of Megabytes.

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Data Access Management System in Azure Blob Storage and AWS S3 Multi-Cloud Storage Environments

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