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[Computational-biology] CFP: IEEE International Workshop on Privacy Aspects of Data Mining

Francesco Bonchi francesco.bonchi at isti.cnr.it
Fri May 26 06:53:10 EST 2006

             PADM'06 - IEEE International Workshop on
                  Privacy Aspects of Data Mining
                        December 18, 2006
           URL: http://www-kdd.isti.cnr.it/padm06/

      At the 2006 IEEE International Conference on Data Mining
                       Hong Kong, December 18-22



o Formal workshop proceedings will be published by IEEE CS press.

o Revised and extended version of some (5-6) selected papers will be
invited for publication on a Special Issue on the
Data & Knowledge Engineering (DKE) journal (Elsevier).

o Papers rejected by the ICDM main conference, can be reconsidered for
acceptance by our workshop (option @ ICDM paper submission time).

Important dates
o July 30, 2006: Submission deadline
o September 8, 2006: Author notification
o September 29, 2006: Submission of Camera-ready papers
o December 18, 2006: Workshop

Brief Desription
Privacy is essential for the provision of electronic and knowledge-based
services in modern e-business, e-commerce, e-government, and e-health
environments. Nowadays, service providers can easily track an
individual's actions, behaviors, and habits.  Given large data
collections of person-specific information, providers can data mine to
learn patterns, models, and trends that can be used to provide
personalized services.  The potential benefits of data mining are
substantial, but it is evident that the collection and analysis of
sensitive personal data arouses concerns about citizens' privacy,
confidentiality and freedom.

When addressed at a technical level, privacy-awareness fosters the
dissemination and adoption of emerging knowledge-based applications.
Obtaining the potential benefits of data mining with a privacy-aware
technology can enable a wider social acceptance of a multitude of new
services and applications based on the knowledge discovery process.
Source data of particular importance include, for instance, biomedical
patient data, web usage log data, mobility data from wireless and sensor
networks: in each case there exist substantial privacy threats, as well
as a potential usefulness of knowledge discovered from these data.

Privacy protection in data mining is a crucial issue that has captured
the attention of many researchers and administrators across a large
number of application domains. Despite such efforts there are still many
open issues that deserve further investigation.  The workshop hopes to
gather researchers and practitioners interested
in the privacy aspects of data mining, both by a technical, and
a social and legal point of views. We hope to attract interest from
a wide range of possible data mining subareas, including: web mining,
medical data mining, spatio-temporal data mining, ubiquitous
knowledge discovery, and obviously, privacy-preserving data mining.

The workshop will seek submissions that cover aspects of privacy
protection solutions and threats as they pertain to various data mining
endeavors. The following comprises a sample, but not complete, listing
of topics:

o Biomedical and healthcare data mining research privacy
o Cryptographic tools for privacy preserving data mining
o Inference and disclosure control for data mining
o Learning algorithms for randomized/perturbed data
o Legal and regulatory frameworks for data mining and privacy
o Privacy and anonymity in e-commerce and user profiling
o Privacy aspects of business processes and enterprise management
o Privacy aspects of geographic, spatial, and temporal data
o Privacy aspects of ubiquitous computing systems
o Privacy enhancement technologies in web environments
o Privacy policy infrastructure, enforcement, and analysis
o Privacy preserving link and social network analysis
o Privacy preserving applications for homeland security
o Privacy preserving data integration
o Privacy protection in fraud and identify theft prevention
o Privacy threats due to data mining
o Query systems and access control
o Trust management for data mining

Paper Submission
Papers will be submitted to the ICDM06 conference cyberchair systems:
more details coming soon. The submitted manuscript should closely
reflect the final paper as it will appear in the Proceedings.

Papers should not exceed 12 pages (pdf or MS-Word) in the IEEE 2-column
format (see the IEEE Computer Society Press Proceedings Author
Guidelines at http://www.computer.org/cspress/instruct.htm)
Submitted papers will be evaluated by at least two reviewers.

Program Chairs
* Francesco Bonchi, KDD Lab, ISTI-C.N.R., Pisa, Italy
* Bradley Malin, Carnegie Mellon University, Pittsburgh, USA
* Yucel Saygin, Sabanci University, Istanbul, Turkey

Program Committee
* Roberto Bayardo, Google, Inc., Mountain View, USA
* Elisa Bertino, Purdue University, West Lafayette, USA
* Peter Christen, Australian National University, Canberra, Australia
* Wenliang (Kevin) Du, Syracuse University, Syracuse, USA
* Elena Ferrari, University of Insubria, Como, Italy
* Fosca Giannotti, ISTI-C.N.R., Pisa, Italy
* Murat Kantarcioglu, University of Texas, Dallas, USA
* Helger Lipmaa, University of Tartu, Estonia
* Stan Matwin, University of Ottawa, Canada
* Michael May, Fraunhofer AIS, Sankt Augustin, Germany
* Dino Pedreschi, University of Pisa, Italy
* Latanya Sweeney, Carnegie Mellon University, Pittsburgh, USA
* Bhavani Thuraisingham,  University of Texas at Dallas, USA
* Vicenç Torra, Spanish Scientific Research Council, Bellaterra, Spain
* Jaideep Vaidya, Rutgers University, New Brunswick, USA
* Vassilios Verykios, University of Thessaly, Volos, Greece
* Staal Vinterbo, Harvard Medical School, Boston, USA
* Jeffrey Yu, Chinese University of Hong Kong

For additional information, please visit the Workshop web site at:


For inquiries, please contact us at: padm06 at isti.cnr.it

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