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Efficient Privacy-Preserving Identity Scheme for Electronic Validation of Phase 1 Clinical Trials

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Book cover E-Technologies (MCETECH 2015)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 209))

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Abstract

New drug studies are essential to advance the pharmaceutical industry’s ability to fight diseases. These studies are typically performed in four phases. We are interested in “phase 1” clinical trials where the goal is to evaluate the safety of a new drug. Contract research organizations recruit participants for their studies and need to verify electronically certain criteria without revealing the identity of these participants to other organizations. We outline some potential attacks against current identity representation schemes. Afterwards, we present privacy-preserving techniques to represent the identity of a participant in a scheme where operations can be performed efficiently and accurately. Our methods and scheme can also be applied to other domains to preserve an individual’s privacy.

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Author information

Authors and Affiliations

  1. School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Canada

    Hanna Farah & Daniel Amyot

  2. Electronic Health Information Laboratory, Children’s Hospital of Eastern Ontario Research Institute, Ottawa, Canada

    Khaled El Emam

Authors
  1. Hanna Farah
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  2. Daniel Amyot
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  3. Khaled El Emam
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Corresponding author

Correspondence to Daniel Amyot .

Editor information

Editors and Affiliations

  1. University of Ottawa, Ottawa, Ontario, Canada

    Morad Benyoucef

  2. Carleton University, Ottawa, Ontario, Canada

    Michael Weiss

  3. Université du Québec à Montréal, Montreal, Québec, Canada

    Hafedh Mili

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© 2015 Springer International Publishing Switzerland

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Farah, H., Amyot, D., Emam, K.E. (2015). Efficient Privacy-Preserving Identity Scheme for Electronic Validation of Phase 1 Clinical Trials. In: Benyoucef, M., Weiss, M., Mili, H. (eds) E-Technologies. MCETECH 2015. Lecture Notes in Business Information Processing, vol 209. Springer, Cham. https://doi.org/10.1007/978-3-319-17957-5_12

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  • DOI: https://doi.org/10.1007/978-3-319-17957-5_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-17956-8

  • Online ISBN: 978-3-319-17957-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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