TrustCell: towards the end-to-end trustworthiness in data-oriented scientific computing

Data-driven computational science on community computational resources is frequently of a magnitude and scale that it requires that computations be done remotely, generating resulting data collections that are too large to be shipped back to a user´s workstation. Service-oriented middleware is well equipped to carry out actions on behalf of a user, but SOA middleware does not address user trust in the privacy of their actions and security of their data. In this paper, we first identify the role of trust in a large distributed computation then develop a model that represents the trust relationship between the users and their remote resources in the grid system. We show how one can construct a trusted relationship from the model, with an emphasis on the importance of context to a specific trust relationship. We provide a case study of a data-driven scientific application that executed across multiple organizations