Multiparty Differential Privacy via Aggregation of Locally Trained Classifiers

  title={Multiparty Differential Privacy via Aggregation of Locally Trained Classifiers},
  author={Manas A. Pathak and Shantanu Rane and Bhiksha Raj},
As increasing amounts of sensitive personal information finds its way into data repositories, it is important to develop analysis mechanisms that can derive aggregate information from these repositories without revealing information about individual data instances. Though the differential privacy model provides a framework to analyze such mechanisms for databases belonging to a single party, this framework has not yet been considered in a multi-party setting. In this paper, we propose a privacy… CONTINUE READING
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Scott Patterson . Privacy - preserving decision trees over vertically partitioned data

  • Jaideep Vaidya, Murat Kantarcioglu, Chris Clifton
  • TKDD
  • 2008

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