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Frawley, Cormac (2023) Understanding the Efficacy of Cloud Native Sensitive Data Protection Capabilities. Masters thesis, Dublin, National College of Ireland.
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Abstract
Given commercial and regulatory imperatives the area of Data Protection & Privacy (DPP) is, or should be, of central importance to any organisation storing data considered to be sensitive. Regulatory requirements requiring organisations to ensure that data is correctly identified, classified and protected are now standard in many parts of the world. In order to protect data it is necessary to know where it is located, have a means to classify it and finally have the ability to enforce data protection policies.
Technical controls used to support data identification, classification and protection have generally been classed as Data Loss Prevention (DLP) solutions. While DLP solutions are applicable, and included, in this research the term itself can be restrictive as definitions can differ on what constitutes a DLP solution. A number of definitions include an in-line preventative capability while other definitions are more broad and define DLP as any solution that provides data protection capabilities. For this reason this research paper will use the term Sensitive Data Protection which covers the broader interpretation.
The advent and subsequent acceleration to public cloud platforms has meant that data protection in the cloud has become a critical risk for large numbers of organisations. Locating and classifying sensitive information data within cloud infrastructure solutions is a key security control for organisations and as a result public cloud vendors have responded by providing native Sensitive Data Protection capabilities across their storage offerings.
Given large numbers of organisations will seek to reduce data protection risk through these capabilities it becomes vital to understand the efficacy of the proposed control. This research is intended to compare the functionality and efficacy of these Sensitive Data Protection solutions across the three main public cloud providers. A standardised testing approach will be used across the cloud platforms utilising automated configuration capabilities and allowing meaningful comparison of the different vendor capabilities.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Mustafa, Raza Ul UNSPECIFIED |
| Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Cloud computing Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security K Law > KDK Republic of Ireland > Data Protection |
| Divisions: | School of Computing > Master of Science in Cyber Security |
| Depositing User: | Ciara O'Brien |
| Date Deposited: | 16 Apr 2025 14:41 |
| Last Modified: | 16 Apr 2025 14:41 |
| URI: | https://norma.ncirl.ie/id/eprint/7435 |
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