Computer Sciences Dept.

Goal-Oriented Privacy Preservation

This is a newly funded NSF Cybertrust project, carried out with David DeWitt and Jude Shavlik in CS, Larry Hanrahan (Chief Epidemiologist, State of Wisconsin), and Amy Trentham-Dietz (Population Health Sciences). Sophisticated data analysis and mining techniques are necessary tools for understanding complex datasets in an increasing number of application domains, including bioinformatics, health care, e-commerce, fraud detection, network attacks, and homeland security. The increasing use of these techniques has also created a heightened awareness of their potential for compromising privacy, and the challenge of controlling data access in accordance with privacy policies while enabling useful analysis has emerged as a central and ubiquitous problem. To meet this challenge, we need to go well beyond traditional access-control strategies because analysis and mining techniques can potentially be applied to published data to infer data that is intended to be private. We are investigating the trade-off between privacy and security guarantees and the utility of the published data for specific analysis tasks; we call this goal-oriented privacy preservation.


This project is funded by NSF Cybertrust project.



Principle Investigators:
    Lawrence Hanrahan (Chief Epidemiologist for the State of Wisconsin)
    Amy Trentham-Dietz (Population Health Sciences, UW-Madison)
    David J. DeWitt (Computer Sciences, UW-Madison)
    Raghu Ramakrishnan (Computer Sciences, UW-Madison)
    Jude W. Shavlik (Computer Sciences, UW-Madison)
    Kristen LeFevre (Computer Sciences, UW-Madison)
    Bee-Chung Chen (Computer Sciences, UW-Madison)


  • Kristen LeFevre, Rakesh Agrawal, Vuk Ercegovac, Raghu Ramakrishnan, Yirong Xu, David J. DeWitt. Limiting Disclosure in Hippocratic Databases. VLDB 2004.
  • Kristen LeFevre, David J. DeWitt, Raghu Ramakrishnan. Incognito: Efficient Full-Domain K-Anonymity. SIGMOD Conference 2005.
  • Bee-Chung Chen, Lei Chen, Yi Lin, Raghu Ramakrishnan. Prediction Cubes. VLDB 2005.
  • Bee-Chung Chen, Lei Chen, David R. Musicant, Raghu Ramakrishnan. Learning from Aggregate Views. ICDE 2006.
  • Kristen LeFevre, David J. DeWitt, Raghu Ramakrishnan. Mondrian Multidimensional K-Anonymity. ICDE 2006.


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