[Dbworld] Call for Participation - PADM09
Monday, November 30th, 2009From: “Wei Jiang” (email address not shown)
CALL FOR PARTICIPATION
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PADM’09: 2009 IEEE International Workshop on Privacy Aspects of Data
Mining: From Theory to Practice
A full-day workshop at the 9th IEEE International Conference on Data Mining
(ICDM 2009)
When: December 6th, 2009
Where: Miami, FL, USA
URL: http://cs.utdallas.edu/padm09/index.html
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DETAILED PROGRAM
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[8:45 - 9:00] Opening Remarks
[9:00 - 10:00] Keynote Talk: Prof. Yucel Saygin, Sabanci University
[10:00 - 10:30] Coffee break
[10:30 - 12:00] Session I: Application of Differential Privacy
* Geetha Jagannathan, Krishnan Pillaipakkamnatt, and Rebecca Wright:
A Practical Differentially Private Random Decision Tree Classifier
* Darakhshan Mir and Rebecca Wright:
A Differentially Private Graph Estimator
* Duy Vu and Aleksandra Slavkovic:
Differential Privacy for Clinical Tria Data: Preliminary Evaluations
[12:00 - 13:30] Lunch
[13:30 - 15:00] Session II: Privacy preserving data mining
and anonymization
* Michal Sramka, Reihaneh Safavi-Naini, and Joerg Denzinger:
An Attack on the Privacy of Sanitized Data That Fuses the Outputs
of Multiple Data Miners
* Piotr Andruszkiewicz:
Privacy Preserving Classification with Emerging Patterns
* Jacob Goldberger and Tamir Tassa:
Efficient Anonymizations with Enhanced Utility
[15:00 - 15:30] Break
[15:30 - 17:00] Panel: “Privacy in Databases: From Theory to Practice”
Participants:
Reid Cushman
Assistant Professor
Department of Medicine, University of Miami
http://www6.miami.edu/ethics/Faculty_staff/cushman.html
Michael Froomkin
Professor of Law
University of Miami
http://www.law.tm/
Brad Malin
Assistant Professor of Biomedical Informatics & Computer Science
Vanderbilt University
http://www.hiplab.org/people/malin
Dino Pedreschi
Professor of Computer Science
University of Pisa
http://www.di.unipi.it/~pedre/
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BRIEF DESCRIPTION
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The field of computer science has evolved to incorporate intrinsically
complex social, organizational, and political environments in which
computers are situated. Nowhere is this more apparent, and the influence of
data mining professionals more necessary, than in the often debated arena
of privacy. There is an ever-increasing demand for the incorporation of new
technologies to collect, analyze, and share data on people for a variety of
worthwhile endeavors. However, the traditional knowledge discovery process
is often at odds with an individual’s civil liberties or expectations of
privacy. As such, many governments are struggling to set national and
international policies on privacy for data mining endeavors. The result is
the relationship between privacy and data mining has received significant
attention in the popular media.
Computer science research communities, and data mining in particular, have
increasingly focused on addressing the seemingly conflicting requirements
for privacy and knowledge discovery. From a methodological perspective,
computer scientists have proposed various statistical, cryptographic, and
databases processing approaches that enable data mining goals without
sacrificing the privacy of the individuals to whom the data corresponds. In
industry, we have witnessed major corporations, many of which are key
supporters of data mining allocating significant resources to study and
develop commercial products that address these issues. These efforts have
only scratched the surface of the problem-space, and there remain many open
research issues for further investigation. While the issues are grounded in
the real-world and concern academia, industry, government, and society in
general, we have yet to witness significant technology transfer and the
application of such techniques to real world environments remains limited.
Clearly, there remain significant opportunities and challenges for the
design and evaluation of privacy respective data mining applications. In
this workshop, we welcome novel research addressing these challenges.
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INQUIRY
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Any questions regarding the workshop should be directed to the organizers
at padm09@utdallas.edu
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