2nd Workshop on
Privacy Preserving Data Mining (PPDM)

Privacy Preserving Data Mining (PPDM)

In the light of developments in technology to analyze personal data, public concerns regarding privacy are rising. While some believe that statistical and Knowledge Discovery and Data Mining (KDDM) research is detached from this issue, we can certainly see that the debate is gaining momentum as KDDM and statistical tools are more widely adopted by public and private organizations hosting large databases of personal records. One of the key requirements of a data mining project is access to the relevant data. Privacy and Security concerns can constrain such access, threatening to derail data mining projects. This workshop will bring together researchers and practitioners to identify problems and solutions where data mining interferes with privacy and security.

Topics of Interest

• Learning from perturbed/obscured data.
• Techniques for protecting confidentiality of sensitive information, including work on statistical databases, and obscuring or restricting data access to prevent violation of privacy and security policies.
• Learning from distributed data sets with limits on sharing of information.
• Hiding knowledge in data sets.
• Underlying methods and techniques to support data mining while respecting privacy and security (e.g., secure multi-party computation).
• The relationship between privacy and knowledge discovery, and algorithms for balancing privacy and knowledge discovery.
• Meanings and measuring of ``privacy'' in privacy-preserving data mining.
• Use of data mining results to reconstruct private information, and corporate security in the face of analysis by KDDM and statistical tools of public data by competitors.
• Use of anonymity techniques to protect privacy in data mining.

Important Dates

Organizers

• Wenliang (Kevin) Du (Chair)
  Syracuse University
  Department of Electrical Engineering and Computer Science
  Syracuse, NY 13244 USA
  Tel: +1 315-443-9180, Fax: +1 315-443-1122
  Email: wedu@ecs.syr.edu
• Chris Clifton (Co-Chair)
  Purdue University
  Department of Computer Sciences
  West Lafayette, Indiana 47907-1398 USA
  Tel: +1 765-494-6005, Fax: +1 765 494-0739
  Email:

Program Committee

• Wesley Chu, University of California, Los Angeles
• George Cybenko, Dartmouth College
• Vladimir Estivill-Castro, Griffith University
• Johannes Gehrke, Cornell University
• Tom Johnsten, University of South Alabama
• Hillol Kargupta, University of Maryland Baltimore County
• Stanley R. M. Oliveira, Embrapa Information Technology
• Benny Pinkas, Trusted Systems Lab, HP Labs
• Vijay V. Raghavan, University of Louisiana Lafayette