Now showing items 1-3 of 3

    • Multidimensional K-Anonymity 

      LeFevre, Kristen; DeWitt, David J.; Ramakrishnan, Raghu (University of Wisconsin-Madison Department of Computer Sciences, 2005)
      K-Anonymity has been proposed as a mechanism for privacy protection in microdata publishing, and numerous recoding ?models? have been considered for achieving kanonymity. This paper proposes a new multidimensional model, ...
    • Privacy Skyline: Privacy with Multidimensional Adversarial Knowledge 

      Chen, Bee-Chung; LeFevre, Kristen; Ramakrishnan, Raghu (University of Wisconsin-Madison Department of Computer Sciences, 2007)
      Privacy is an important issue in data publishing. Many organizations distribute non-aggregate personal data for research, and they must take steps to ensure that an adversary cannot predict sensitive information pertaining ...
    • Scalable Anonymization Algorithms for Large Data Sets 

      LeFevre, Kristen; DeWitt, David (University of Wisconsin-Madison Department of Computer Sciences, 2007)
      k-Anonymity is a widely-studied mechanism for protecting identity when distributing non-aggregate personal data. This basic mechanism can also be extended to protect an individual-level sensitive attribute. Numerous ...