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Privacy Protection through Computational Workflows
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Description
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While there is a plethora of mechanisms to ensure lawful access to
privacy-protected data, additional research is required in order to
reassure individuals that their personal data is being used for
the purpose that they consented to. This is particularly
important in the context of new data mining approaches, as used, for
instance, in biomedical research and commercial data mining.
In this project we investigate the use of computational workflows to
ensure and enforce appropriate use of sensitive personal
data.
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Status
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We are currently looking for collaboration and funding
opportunities for this project.
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Research
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The goal is to enable the Wings Workflow Systems to support a
variety of privacy related tasks. This requires the development
of a usage-oriented policy language, the extension of the Wings
system in order to enforce such policies during workflow
generation and execution, and the development of a theory of
policy negotiation.
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Publications
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- "Reasoning about the Appropriate Use of Private Data through Computational Workflows", Yolanda Gil, Christian Fritz. In AAAI Spring Symposium on Privacy Management, Stanford, CA, March 23-25, 2010
- Privacy Enforcement in Data Analysis Workflows, Yolanda Gil, William K. Cheung, Varun Ratnakar, Kai-kin Chan. In 2007 Workshop on Privacy Enforcement and Accountability with Semantics (PEAS'07), held in conjunction with the Sixth International Semantic Web Conference (ISWC'07) and the Second Asian Semantic Web Conference (ASWC'07), Busan, Korea, November 11-15, 2007
- Towards Privacy Aware Data Analysis Workflows for e-Science, William Cheung, Yolanda Gil. In 2007 Workshop on Semantic e-Science (SeS2007), held in conjunction with the Twenty-Second Conference of the Association for the Advancement of Artificial Intelligence (AAAI), Vancouver, British Columbia, Canada, July 22-26, 2007
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Demo
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See a demo -->
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People
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Group Members:
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Funding
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Links
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