PREVENTION OF LEAKAGE SENSITIVE AND PRIVILEGED INFORMATION ANALYSIS

Authors

  • Abhijeet kumar M.Tech Scholar CSE, Compucom Inst. Of Tech. & Management,jaipur
  • Mrs.Geeta Tiwari Asst. Prof CSE Compucom Inst. Of Tech. & Management,jaipur
  • Mr.kishore Mishra Asst. Prof CSE Compucom Inst. Of Tech. & Management,jaipur

Keywords:

Data mining, Anonymization , Fuzzy C-Means Clustering, Privacy preserving.

Abstract

privacy preserving is the most concerning issue. Information related to specific individual needs to be protected, so that it may not harm the privacy. Anonymization method is applied on the dataset, Pseudonymization is a method to substitute identifiable data with a reversible, consistent value. Anonymization is the destruction of the identifiable data. K-anonymity has been used as successful technique it express this methodology achieves enhanced over the distinct l-diversity measure, probabilistic l-diversity measure and k-anonymity through t-closeness measure since only rarer partitioning must be done for a robust secrecy requirement. Then by using of fuzzy c-means clustering data are clustered.

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Published

2021-11-22

How to Cite

kumar, A., Tiwari, M., & Mishra, M. (2021). PREVENTION OF LEAKAGE SENSITIVE AND PRIVILEGED INFORMATION ANALYSIS. International Journal of Technical Innovation in Modern Engineering & Science, 5(1), 367–370. Retrieved from https://ijtimes.com/index.php/ijtimes/article/view/2270