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Hiding outliers into crowd: Privacy-preserving data publishing with outliers

  • Published:2015-11 Issue: Volume:100 Page:94-115
  • ISSN:0169-023X
  • Container-title:Data & Knowledge Engineering
  • language:en
  • Short-container-title:Data & Knowledge Engineering

Author:

Wang Hui (Wendy),Liu Ruilin

Publisher

Elsevier BV

Subject

Information Systems and Management

Reference71 articles.

1. k-anonymity: a model for protecting privacy;Sweeney;Int. J. Uncertain. Fuzziness Knowl. Based Syst.,2002

2. The price of privately releasing contingency tables and the spectra of random matrices with correlated rows;Kasiviswanathan,2010

3. Generalizing data to provide anonymity when disclosing information;Samarati,1998

4. L-diversity: Privacy beyond k-anonymity;Machanavajjhala;ACM Trans. Knowl. Discov. Data,2007

5. t-closeness: Privacy beyond k-anonymity and l-diversity;Li,2007

Cited by 18 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A multiple sensitive attributes data publishing method with guaranteed information utility;CAAI Transactions on Intelligence Technology;2023-05-27

2. A privacy‐preserving method for publishing data with multiple sensitive attributes;CAAI Transactions on Intelligence Technology;2023-03-09

3. A New Privacy-Preserving Data Publishing Algorithm Utilizing Connectivity-Based Outlier Factor and Mondrian Techniques;Computers, Materials & Continua;2023

4. k-Means Clustering with Optimal Centroid: An Optimization Insisted Model for Removing Outliers;International Journal of Pattern Recognition and Artificial Intelligence;2022-06-20

5. Medical data publishing based on average distribution and clustering;CAAI Transactions on Intelligence Technology;2022-04-22
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