Department of Computer Science and Engineering Bannari Amman Institute of Technology, Erode, Tamil Nadu
Abstract
Privacy protection is a high level of encouragement to provide confidential information by posting the details of the customers. Data mining tasks are incorporated in the database for data intelligence and the knowledge recovery. Initially different isolated transformation techniques are proposed for masking the sensitive information, which combines correlation analysis and data transformation provides intended level of privacy preservation. In this research work correlation based transformation techniques are considered to preserve the sensitive information and provides the complete privacy of the original information. The classifiers Decision Tree (DT), Random Forest(RF), Linear model, Ada Boost, Support Vector Machine and Neural Network are used to identify the performance of the proposed works.
Saranya, K., & Premalatha, K. (2021). Correlation Based Transformation For Privacy Preserving Medical Data Publication. Int. J. of Aquatic Science, 12(3), 1038-1046.
MLA
K. Saranya; K. Premalatha. "Correlation Based Transformation For Privacy Preserving Medical Data Publication". Int. J. of Aquatic Science, 12, 3, 2021, 1038-1046.
HARVARD
Saranya, K., Premalatha, K. (2021). 'Correlation Based Transformation For Privacy Preserving Medical Data Publication', Int. J. of Aquatic Science, 12(3), pp. 1038-1046.
VANCOUVER
Saranya, K., Premalatha, K. Correlation Based Transformation For Privacy Preserving Medical Data Publication. Int. J. of Aquatic Science, 2021; 12(3): 1038-1046.
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