On Privacy Preserving Data Mining Techniques: Merits and Demerits

Authors

  • Mohana Chelvan P Dept. of Computer Science, Hindustan College of Arts and Science, Chennai, India
  • Perumal K Dept. of Computer Applications, Madurai Kamaraj University, Madurai, India

DOI:

https://doi.org/10.26438/ijcse/v5i9.210214

Keywords:

privacy-preserving data mining, k-anonymity, l-diversity, t-closeness, slicing

Abstract

Data mining is the process that extracts previously not known valid and actionable information from large archived data to make crucial business and strategic decisions. In recent years, privacy preserving data mining techniques has been studied and more research has been done in this area due to proliferation of internet in everyday life along with huge availability of personal data. Huge volume of microdata is produced on every minute due to e-governance and e-commerce which contains private data about individuals and businesses. The data has been modified in some way to preserve the privacy of individuals. The main goal of privacy preserving data mining is hiding an individual’s sensitive identity and at the same time maintains the usability of data. This paper will give an overview about these rapidly changing techniques and their advancements.

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Published

2025-11-12
CITATION
DOI: 10.26438/ijcse/v5i9.210214
Published: 2025-11-12

How to Cite

[1]
P. Mohana Chelvan and K. Perumal, “On Privacy Preserving Data Mining Techniques: Merits and Demerits”, Int. J. Comp. Sci. Eng., vol. 5, no. 9, pp. 210–214, Nov. 2025.

Issue

Vol. 5 No. 9 (2017): IJCSE September Edition

Section

Review Article

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