Effectiveness and Limitations of existing techniques for privacy preservation data mining (PPDM) for Medical Data

  • Amol R Kulkarni
  • Kamepalli Sujatha
Keywords: Privacy Preservation Data Mining, homomorphic encryption, federated learning, secured multiparty computation.


This survey paper examines the application of Federated Learning (FL) and secure Multiparty Computing (MPC) considering medical data privacy, further provides an overview of FL and MPC techniques and discusses their strengths and weaknesses. This also covers other techniques like Homomorphic Encryption, data masking, differential privacy for its efficiency, and limitations.


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How to Cite
Kulkarni, A. R., & Sujatha, K. (2023). Effectiveness and Limitations of existing techniques for privacy preservation data mining (PPDM) for Medical Data. Asian Journal For Convergence In Technology (AJCT) ISSN -2350-1146, 9(2), 57-66. https://doi.org/10.33130/AJCT.2023v09i02.010

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