Information Security Tech. Report
A fuzzy model for calculating workflow trust using provenance data
Proceedings of the 15th ACM Mardi Gras conference: From lightweight mash-ups to lambda grids: Understanding the spectrum of distributed computing requirements, applications, tools, infrastructures, interoperability, and the incremental adoption of key capabilities
Provenance Provisioning in Mobile Agent-Based Distributed Job Workflow Execution
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007
Securing Grid Workflows with Trusted Computing
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part III
The Foundations for Provenance on the Web
Foundations and Trends in Web Science
PrIMe: A methodology for developing provenance-aware applications
ACM Transactions on Software Engineering and Methodology (TOSEM)
Some thoughts on using argumentation to handle trust
CLIMA'11 Proceedings of the 12th international conference on Computational logic in multi-agent systems
Towards Next Generation Provenance Systems for e-Science
International Journal of Information System Modeling and Design
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Provenance is the documentation concerning the origin of a result generated by a process, and provides explanations about who, how, what resources were used in a process, and the processing steps that occurred to produce the result. Such provenance information is important to improve a scientist's ability to judge and place certain amount of trust on the generated data. We illustrate how provenance information associated with a workflow can be used to evaluate trust. This work is based on several use cases from a Bio-Diversity application. We also propose a simple architecture to illustrate our trust framework.