@inproceedings{ Davidson2010,
  author = {Davidson, Susan B and Khanna, Sanjeev and Roy, Sudeepa and Boulakia,
	Sarah Cohen},
  title = {{Privacy issues in scientific workflow provenance}},
  booktitle = {First International Workshop on Workflow Approaches to New Data-centric
	Science (WANDS'10)},
  year = {2010},
  editor = {Missier, Paolo and Curcin, Vasa and Dadvidson, Susan},
  address = {Indianapolis},
  publisher = {ACM},
  abstract = {A scientific workflow often deals with proprietary modules as well
	as private or confidential data, such as health or medical information.
	Hence providing exact answers to provenance queries over all executions
	of the workflow may reveal private information. In this paper we
	first study the potential privacy issues in a scientific workflow
	-- module privacy, data privacy, and provenance privacy, and frame
	several natural questions: (i) can we formally analyze module, data
	or provenance privacy giving provable privacy guarantees for an unlimited/bounded
	number of provenance queries? (ii) how can we answer provenance queries,
	providing as much information as possible to the user while still
	guaranteeing the required privacy? Then we look at module privacy
	in detail and propose a formal model from our recent work in [11].
	Finally we point to several directions for future work.},
  keywords = {#disease_outbreak,#management,#privacy,#provenance,#use,#workflow},
  mendeley-tags = {#disease_outbreak,#management,#privacy,#provenance,#use,#workflow},
  url = {http://portal.acm.org/citation.cfm?id=1833398.1833401}
}

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