Ensuring Data Confidentiality of Workflows in Computer Clouds: Heuristic and Exact Approaches

Cloud computing provides an on-demand environment that allows users to execute their local workflows in an elastic and highly available environment. Various applications can be modeled as workflows, many of which are compute- and data-intensive. In the cloud, the storage location of this data becomes a concern when confidentiality might be compromised. Malicious users can make inferences about the results and the structure of the workflows. Data dispersion, encryption, and other mechanisms can be adopted to enhance data privacy, but these cannot be implemented without considering the workflow scheduling, as this risks significantly increasing execution time and financial cost. In this paper, we introduce CYCLOPS, an approach that aims to execute workflows in cloud computing environments efficiently while considering the confidentiality constraints of the produced data and the workflow structure.