To be Held in Conjunction with the
Fourth IEEE International Conference on Data Mining
(ICDM 2004)
Datamining and Disclosure Limitation for Categorical Statistical Database
Rapid growth of information technologies nowadays has brought tremendous opportunities for data sharing and integration, and also demands for privacy protection. The goal of this workshop is to discuss issues of privacy and security in data mining, synergize different views of techniques and policies, and brainstorm future research directions. Although techniques, such as random perturbation, cryptographic-based methods, and database inference control have been developed, many of the key problems still remain open in this area. Especially, new privacy and security issues have been identified, and the scope of this problem has been expanded. In addition to these existing technologies, people attempt to explore new approaches to tackle the problem. Furthermore, special techniques may be needed to deal with some data mining applications, such as privacy-preserving mining of imbalanced data, bioinformatics data, streaming data, etc. We believe that it would be valuable to both the privacy and security community and the data mining community to examine the progress achieved in this area. We strongly encourage researchers with interest in the areas of privacy and security as well as data mining and machine learning to attend the workshop.
- Privacy and security protection during the phase of data collection, including privacy and security policies, data ownership, identity theft protection.
- Access control techniques and secure data models.
- Secure learning algorithms for randomized/perturbed data.
- Privacy-Preserving multi-party data mining.
- Trust management for data mining.
- Learning from imbalanced data, streaming data, and bioinformatics data while preserving data privacy.
- Inference/disclosure related data mining.
- Privacy protection in E-Commerce.
- Privacy laws for fraud detection and for protecting personal data, medical data, and the public release of data.
- Secure link analysis and social network analysis.
- Data mining applications for terrorist detection.
- Privacy enhancement technologies in web environments.
- Privacy guarantees and usability of perturbation/randomization techniques.
- Analysis of confidentiality control methods.
Please send an electronic submission (postscript or PDF versions) to psdm@itd.nrl.navy.mil and cc zhizhan@site.uottawa.ca. Papers should be prepared in the same format as ICDM conference papers and adhere to a 10 page limit.
The accepted papers will be published in the ICDM workshop proceedings. Information about the workshop will be available via a link to the main conference site. The presentation slides will be posted on the web.
At least one of authors of accepted papers must present their paper at the workshop.
Elisa Bertino, Purdue University, USA
Chris Clifton, Purdue University, USA
Ping Chen, University of Houston Downtown, USA
Steve Fienberg, Carnegie-Mellon University, USA
Tom Goldring, National Security Agency, USA
Mike Just, Carleton University, Canada
Helger Lipmaa, Helsinki University of Technology, Finland
Kobbi Nissim, Microsoft, USA
Pierangela Samarati, Universita` degli Studi di Milano, Italy
Jaideep Vaidya, Rutgers University, USA
Vassilis Verykios, University of Thessaly, Greece
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Stan Matwin School of Information Technology & Engineering, University of Ottawa Ottawa, Ontario, Canada K1N 6N5 Phone: (613)562-5800 ext.6679 Fax: (613) 562-5664 |
LiWu Chang Naval Research Laboratory, Code 5540 Washington, DC 20375 U.S.A. Phone: (202)404-8224 Fax: (202)404-1167 |
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Carlisle Adams School of Information Technology & Engineering University of Ottawa Ottawa, Ontario, Canada K1N 6N5 Phone: (613) 562-5800 ext. 2345 Fax: (613) 562-5664 |
Justin Zhan School of Information Technology & Engineering University of Ottawa Ottawa, Ontario, Canada K1N 6N5 Phone: (613)562-5800 ext.2513 Fax: (613) 562-5664 |
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Last modified on July 9, 2004.