Privacy preserving publication of relational and transaction data: Survey on the anonymization of patient data

@article{Puri2019PrivacyPP,
  title={Privacy preserving publication of relational and transaction data: Survey on the anonymization of patient data},
  author={Vartika Puri and Shelly Sachdeva and Parmeet Kaur},
  journal={Comput. Sci. Rev.},
  year={2019},
  volume={32},
  pages={45-61}
}
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Investigations show that the validity analysis model of multirelational data clustering based on credible probability is more effective in practice and satisfies the research goals entirely.
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This chapter presents several aspects regarding IoT (Internet of Things) and communication technology synergies for remote services in healthcare for patients with higher risks that justify remote monitoring, taking into account the risks for data security that appears in the case of these applications.
( k , m , t )‐anonymity: Enhanced privacy for transactional data

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