Privacy Preservation with Penalty in Decentralized Network Using Multiparty Computation

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Provided by: AICIT
Topic: Big Data
Format: PDF
Privacy is an important issue in many peer to peer data mining applications. Analysis of privacy sensitive data in privacy preserving data mining is a challenging task. It is often assumed that parties in a multiparty environment are well behaved and sustain with predefined protocols. Each party has certain responsibilities for performing their computation, communicating correct values to others and protecting the privacy of the data. They should not conspire with data of other parties during computation or communication. The assumptions of well-behaved parties fail to translate to real life application, where self-interested parties try to maximize their own benefit, even if they conspire.
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