Corpus ID: 212540080

Clustering Based L-Diversity Anonymity Model for Privacy Preservation of Data Publishing

@inproceedings{Malaisamy2016ClusteringBL,
  title={Clustering Based L-Diversity Anonymity Model for Privacy Preservation of Data Publishing},
  author={A. Malaisamy and D. K. Nawaz},
  year={2016}
}
Privacy preservation data publication has received great attention in both the database community and theory community in recent years. Data publishing provides easiness for data exchange and data sharing. But, the personal privacy information leakage issues have become progressively more prominent. Anonymous algorithm is key technique to realize the privacy protection in data publishing environment. In addition, the anonymity algorithm of all sensitive attributes values is treated by lacking… Expand
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SHOWING 1-10 OF 19 REFERENCES
Privacy-preserving data publishing for cluster analysis
  • 77
  • PDF
A comprehensive review on privacy preserving data mining
  • 64
Privacy-preserving distributed clustering
  • 28
  • Highly Influential
  • PDF
Privacy Preserving Techniques in Social Networks Data Publishing-A Review
  • 11
...
1
2
...