Cloud computing technology framework and reducing risks

Bc. Khaled Ali Ahmed Akrir

Doctoral thesis

Anotácia:

The thesis investigates, in a qualitative way, the vectors that contribute to cloud computing risks in the areas of security, business, and compliance. The focus of this research is on the identification of risk vectors that affect cloud computing and the creation of a framework that can help IT managers in their cloud adoption process. Economic pressures on businesses are creating a demand for an alternative delivery of the model that can provide flexible payments, dramatic cuts in capital investment, and reductions in operational cost. Cloud computing is positioned to take advantage of these economic pressures with low cost IT services and a flexible payment model, but at what risk to the business? Security concerns about cloud computing are heightened and fueled by misconceptions related to security and compliance risks. Unfortunately, these security concerns are seldom, expressed quantifiably. To bring clarity to cloud computing security, compliance, and business risks, this research focuses on a qualitative analysis of risk vectors drawn from one-on-one interviews with top IT experts selected. The qualitative aspect of this research separates facts from unfounded suspicions, and creates a framework that can help align perceived risks of cloud computing with actual risks. The qualitative research was done through interviews with experts and through the survey to measure risk perceptions about cloud computing using a Likert scale. The decision-making model and the framework created by this research help to rationalize the risk vectors on cloud environments and recommend reducing strategies to bring the IT industry one step closer to a clearer understanding of the risks-tradeoffs implications of cloud computing environments.

Abstract:

The thesis investigates, in a qualitative way, the vectors that contribute to cloud computing risks in the areas of security, business, and compliance. The focus of this research is on the identification of risk vectors that affect cloud computing and the creation of a framework that can help IT managers in their cloud adoption process. Economic pressures on businesses are creating a demand for an alternative delivery of the model that can provide flexible payments, dramatic cuts in capital investment, and reductions in operational cost. Cloud computing is positioned to take advantage of these economic pressures with low cost IT services and a flexible payment model, but at what risk to the business? Security concerns about cloud computing are heightened and fueled by misconceptions related to security and compliance risks. Unfortunately, these security concerns are seldom, expressed quantifiably. To bring clarity to cloud computing security, compliance, and business risks, this research focuses on a qualitative analysis of risk vectors drawn from one-on-one interviews with top IT experts selected. The qualitative aspect of this research separates facts from unfounded suspicions, and creates a framework that can help align perceived risks of cloud computing with actual risks. The qualitative research was done through interviews with experts and through the survey to measure risk perceptions about cloud computing using a Likert scale. The decision-making model and the framework created by this research help to rationalize the risk vectors on cloud environments and recommend reducing strategies to bring the IT industry one step closer to a clearer understanding of the risks-tradeoffs implications of cloud computing environments.

Kľúčové slová

CSRF, CBRF, CCRF, Cloud computing

Keywords

Cloud computing, CSRF, CBRF, CCRF

Jazyk práce: Czech

Datum vytvoření / odevzdání či podání práce: 8. 9. 2015

Obhajoba závěrečné práce

• Vedúci: doc. Ing. Zdeněk Havlíček, CSc.
• Oponent: Tomáš Macák, doc. Ing., Ph.D., Antonín Slabý, externi, Jiří Feuerlicht, Ing., externi

Czech University of Life Sciences Prague

Faculty of Economics and Management

Doctoral programme / odbor:
Systems Engineering and Informatics / Information Management