DCloud – FWF P 26289-N23

The increasing distribution of cloud services comes with significant benefits but also substantial risks to privacy and security.

The goal of this project was to develop a decision framework model regarding the adaption of and the migration to cloud-based systems into existing infrastructure.

We created a taxonomy of social engineering attacks to classify attacks. Social Engineering is one the most important attack vectors against “knowledge workers”. Moreover, it is important to understand how social engineering attack scenarios differ when system infrastructure components are migrated into the cloud. In addition, we looked at important components such as the network work infrastructure to build components of the decision framework and a process for migration and autonomic management. We then extended extends the state of the art by providing insights into the migration needs and risks that that hinder cloud migration in a corporate environment.

Based on these finding we developed a software prototype to support an effective, fast and well-informed decision based on the risks of a migration to the cloud. The tool also estimates risks and determines cost associated with specific requirements.

We finally evaluated both the theoretical framework and the prototype implementation in two real-world use cases industrial contexts by applying both Theo case study research method and action research.

This project was funded by the Austrian Science Fund (FWF) P 26289-N23.

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