The role of user defined function in privacy preserving data mining

  • Authors

    • G Manikandan SASTRA DEEMED University
    • A Vamsi Krishna SASTRA DEEMED University
    • P Lakshmana Sarvagna SASTRA DEEMED University
    2018-06-01
    https://doi.org/10.14419/ijet.v7i2.12202
  • Clustering, Misclassification error, Privacy, Scaling, Shearing, Translation

  • Abstract

    Data mining is used to retrieve the plugged in information from the huge data warehouse. Data mining techniques use wide variety of tools for extracting the required knowledge from the hefty data warehouse. Many organizations trust on the extracted knowledge for strategical decision making. In the downside these techniques also reveals some private information as part of the conversion process. Experts rely on various privacy preserving approaches to prevent the data disclosure. This paper primarily focuses on the use of a User-defined Function to maintain data privacy. The output of the proposed approach is compared with the 3-Dimensional geometric transformations such as Translation, Scaling and Shearing. From the experimental outcome it is evident that the proposed approach results in a minimal misclassification error when compared with the other data transformations.

     

  • References

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  • How to Cite

    Manikandan, G., Vamsi Krishna, A., & Lakshmana Sarvagna, P. (2018). The role of user defined function in privacy preserving data mining. International Journal of Engineering & Technology, 7(2), 884-886. https://doi.org/10.14419/ijet.v7i2.12202

    Received date: 2018-04-27

    Accepted date: 2018-05-14

    Published date: 2018-06-01