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Cloud Forensic Framework For IaaS With Support for Volatile Memory

Banas, Matus (2015) Cloud Forensic Framework For IaaS With Support for Volatile Memory. Masters thesis, Dublin, National College of Ireland.

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Cloud computing is attracting large base of users and organisations. However, lack of trust in public cloud providers, especially their legal responsibility towards the legislation in the countries of their origin sometimes complicates the move to the public cloud. Organisations, and communities such as research, education, government, and healthcare incline towards private or community cloud solutions. In those cases organisation, or the members of the community take role of the cloud provider. Similarly to the traditional IT infrastructure, cloud platforms also suffer from potential security related incidents. Regardless of the incident being internal, external, malicious, or accidental, it should be investigated, understood, and prevented from happening again in the future. However, underlying architecture of cloud introduced new challenges in digital forensics and made majority of the traditional forensic tools, and techniques irrelevant. Providers of private and community clouds are often kept in dark, with very limited ability to collect relevant evidence from their platforms. Cloud users on the other hand rely fully on the cooperation of the provider to provide the relevant data. This led to substantial research in the area of cloud forensics over last few years, trying to identify the efficient ways to successfully perform cloud forensics either as a end user, or a provider.

Focus of this thesis is to provide Self-service Forensic Framework for IaaS platforms, and determine the importance of volatile memory forensics in Cloud environment. Our framework allows cloud users, and cloud providers to extract disk, and memory images for forensic investigation in efficient, effective, and secure way.

Item Type: Thesis (Masters)
Subjects: T Technology > T Technology (General) > Information Technology > Cloud computing
Divisions: School of Computing > Master of Science in Cloud Computing
Depositing User: Caoimhe Ní Mhaicín
Date Deposited: 13 Oct 2015 13:24
Last Modified: 05 Feb 2016 10:07

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