A Proposed Technique for Privacy Preservation by Anonymization Method Accomplishing Concept of K-Means Clustering and DES

No abstract is available for this paper.

• Publication year

  2017

• Venue

  International Journal for Research in Applied Science and Engineering Technology

• Publication date

  2017-08-30

• Fields of study

  Computer Science

• Identifiers
  DOI 10.22214/IJRASET.2017.8226
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• An approach for prevention of privacy breach and information leakage in sensitive data mining

  2015cited by this paper
• Survey on Privacy Preserving Data Mining

  2014cited by this paper
• A Review of K-mean Algorithm

  2013cited by this paper
• Survey on Privacy Preserving Data Mining

  2010cited by this paper
• Privacy-preserving data mining: A feature set partitioning approach

  2010cited by this paper
• Protect privacy of medical informatics using k-anonymization model

  2010cited by this paper
• A Survey on Privacy Preserving Approaches in Data Publishing

  2009cited by this paper
• Privacy-preserving data publishing for cluster analysis

  2009cited by this paper
• Identity disclosure protection: A data reconstruction approach for privacy-preserving data mining

  2009cited by this paper
• Towards optimal k-anonymization

  2008cited by this paper
• Privacy-Preserving Data Mining : Developments and Directions

  2004cited by this paper
• k-Anonymity: A Model for Protecting Privacy

  2002cited by this paper

• No citing papers are available for this paper.