A General Survey of Privacy-Preserving Data Mining Models and Algorithms

  title={A General Survey of Privacy-Preserving Data Mining Models and Algorithms},
  author={Charu C. Aggarwal and Philip S. Yu},
  booktitle={Privacy-Preserving Data Mining},
In recent years, privacy-preserving data mining has been studied extensively, because of the wide proliferation of sensitive information on the internet. A number of algorithmic techniques have been designed for privacy-preserving data mining. In this paper, we provide a review of the state-of-the-art methods for privacy. We discuss methods for randomization, k-anonymization, and distributed privacy-preserving data mining. We also discuss cases in which the output of data mining applications… CONTINUE READING
Highly Influential
This paper has highly influenced 13 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 302 citations. REVIEW CITATIONS

From This Paper

Topics from this paper.
172 Citations
135 References
Similar Papers


Publications citing this paper.
Showing 1-10 of 172 extracted citations

303 Citations

Citations per Year
Semantic Scholar estimates that this publication has 303 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 135 references

Privacy Technologies for Homeland Security. Testimony before the Privacy and Integrity Advisory Committee of the Deprtment of Homeland Scurity

  • L. Sweeney
  • 2005
Highly Influential
7 Excerpts

On the Design and Quantification of Privacy- Preserving Data Mining Algorithms

  • C C.AgrawalD.Aggarwal
  • ACM PODS Conference,
  • 2002
Highly Influential
7 Excerpts

Why methods for genomic data privacy fail and what we can do to fix it, AAAS

  • B. Malin
  • Annual Meeting,
  • 2004
Highly Influential
4 Excerpts

Similar Papers

Loading similar papers…