[crypto] [lindac at dimacs.rutgers.edu: BSF/DIMACS/DyDAn Workshop on Data Privacy]

[R. Hirschfeld]

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Date: Mon, 7 Jan 2008 10:08:06 -0500 (EST)
From: Linda Casals <lindac at dimacs.rutgers.edu>
Subject: BSF/DIMACS/DyDAn Workshop on Data Privacy

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BSF/DIMACS/DyDAn Workshop on Data Privacy

      February 4 - 7, 2008
      DIMACS/DyDAn Center, CoRE Building, Rutgers University

Organizers:
      Kobbi Nissim, Ben Gurion University, kobbi at cs.bgu.ac.il 
      Benny Pinkas, University of Haifa, benny at cs.haifa.ac.il 
      Rebecca Wright, Rutgers University, rebecca.wright at rutgers.edu 

Presented under the auspices of the DIMACS Special Focus on 
Communication Security and Information Privacy and 
the Center for Dynamic Data Analysis (DyDAn).

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An ever-increasing amount of data is available in digital form, often
accessible via a network. Not surprisingly, this trend is accompanied
by an increase in public awareness of privacy issues and by
legislation of privacy laws. The interest in privacy, and the tension
between privacy and utility of data, is amplified by our growing
ability to collect and store large amounts of data, and our ability to
mine meaningful information from it. This workshop will view privacy
in a broad sense in order to facilitate interaction and discussion
between privacy-oriented researchers in different communities.

The study of "privacy" is inherently interdisciplinary, spanning a
range of applications and scenarios, such as analysis of census data,
detection and prevention of terrorist activity, and biomedical
research. There is a fundamental interplay between privacy and law,
security, economics, and the social sciences. This workshop will
foster interactions between researchers in these fields with those in
statistics and computer science, toward the goal of developing problem
formulations that can be translated into a technical mathematical
language that lends itself to a more rigorous study of privacy. The
workshop will contrast these formal definitions with more intuitive
notions of privacy from the social sciences, economics, philosophy and
law to determine the extent to which they capture the perceived
meaning of privacy in different settings.

Privacy-preserving technologies may soon become an integral part of
the basic infrastructure for the collection and dissemination of
official statistics, as well as for research in business, economics,
medical sciences, and social sciences. Functional solutions for
preserving privacy would therefore serve as a central part of the
infrastructure for those disciplines. This workshop will address a
variety of questions on algorithms for privacy-preserving analysis
such as:

  * To what extent can such techniques be applied to 
     statistical data?
  * What are the consequences to privacy and confidentiality 
     if such techniques are not used?
  * Are changes in statistical tools needed to make them 
     compatible with such techniques?
  * Can the techniques be modified to allow use of standard 
     statistical tools and practices? 

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Registration:

Pre-registration deadline: January 28, 2008

Please see website for registration information.

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Information on participation, registration, accomodations, and travel 
can be found at:

  http://dimacs.rutgers.edu/Workshops/DataPrivacy/

   **PLEASE BE SURE TO PRE-REGISTER EARLY**

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