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  Published Paper Details:

  Paper Title

PRIVACY PROTECTION USING GENERALIZATION FOR COLLABORATIVE DATA PUBLISHING

  Authors

  Malgireddy Saidireddy

  Keywords

Privacy preserving, data mining, k-anonymity, collaborative data publishing, dynamic programming

  Abstract


Organizations share their data about customers for exploring potential business avenues. The sharing of data has posed several threats leading to individual identification. Owing to this, privacy preserving data publication has become an important research problem. The main goals of this problem are to preserve privacy of individuals while revealing useful information. An organization may implement and follow its privacy policy. But when two companies share information about a common set of individuals, and if their privacy policies differ, it is likely that there is privacy breach unless there is a common policy. One such solution was proposed for such a scenario, based on k-anonymity and cut-tree method for 2-party data. This paper suggests a simple solution for integrating n-party data using dynamic programming on subsets. The solution is based on thresholds for privacy and in formativeness based on k-anonymity

  IJCRT's Publication Details

  Unique Identification Number - IJCRTNCES061

  Paper ID - 180562

  Page Number(s) - 377-382

  Pubished in - Volume 6 | Issue 1 | December - 2017

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Malgireddy Saidireddy,   "PRIVACY PROTECTION USING GENERALIZATION FOR COLLABORATIVE DATA PUBLISHING", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.6, Issue 1, pp.377-382, December - 2017, Available at :http://www.ijcrt.org/papers/IJCRTNCES061.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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