Toward Preserving Results Confidentiality in Cloud-Based
Scientific Workflows
Author/Presenter
Event Type
Workshop
TimeMonday, November 13th2:25pm -
2:50pm
Location501
DescriptionCloud computing has established itself as a solid
computational model that allows for scientists to deploy
their simulation-based experiments on distributed
virtual resources to execute a wide range of scientific
experiments. These experiments can be modeled as
scientific workflows. Many of these workflows are
data-intensive and produce a large volume of data, which
is also stored in the cloud using storage services by
Scientific Workflow Management Systems (SWfMS). One main
issue regarding cloud storage services is
confidentiality of stored data, i.e. if unauthorized
people access data files they can infer knowledge about
the results or even about the workflow structure.
Encryption is a possible solution, but it may not be be
sufficient and a new level of security can be added to
preserve data confidentiality: data dispersion. In order
to reduce this risk, generated data files cannot be
stored in the same bucket, or at least sensitive data
files have to be distributed across many cloud storage.
In this paper, we present IPConf, an approach to
preserve workflow results confidentiality in cloud
storage. IPConf generates a distribution plan for data
files generated during a workflow execution. This plan
disperses data files in several cloud storage to
preserve confidentiality. This distribution plan is then
sent to the SWfMS that effectively stores generated data
into specific buckets during workflow execution.
Experiments performed using real data from SciPhy
workflow executions indicate the potential of the
proposed approach.
Author/Presenter
