Efficient Anonymizations with Enhanced Utility

@article{Goldberger2009EfficientAW,
  title={Efficient Anonymizations with Enhanced Utility},
  author={Jacob Goldberger and Tamir Tassa},
  journal={2009 IEEE International Conference on Data Mining Workshops},
  year={2009},
  pages={106-113}
}
The k-anonymization method is a commonly used privacy-preserving technique. Previous studies used various measures of utility that aim at enhancing the correlation between the original public data and the generalized public data. We, bearing in mind that a primary goal in releasing the anonymized database for data mining is to deduce methods of predicting the private data from the public data, propose a new information-theoretic measure that aims at enhancing the correlation between the… CONTINUE READING
Highly Cited
This paper has 63 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.
32 Citations
23 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 32 extracted citations

64 Citations

01020'12'14'16'18
Citations per Year
Semantic Scholar estimates that this publication has 64 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 23 references

A framework for efficient data anonymization under privacy and accuracy constraints

  • P. Karras, P. Kalnis, N. Mamoulis
  • ACM Trans . Database Syst
  • 2009

Similar Papers

Loading similar papers…