Incentivizing Differentially Private Federated Learning: A Multi-Dimensional Contract Approach

IEEE Internet of Things Journal(2021)

Cited 64|Views32
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Abstract
Federated learning is a promising tool in the Internet-of-Things (IoT) domain for training a machine learning model in a decentralized manner. Specifically, the data owners (e.g., IoT device consumers) keep their raw data and only share their local computation results to train the global model of the model owner (e.g., an IoT service provider). When executing the federated learning task, the data ...
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Key words
Data models,Computational modeling,Collaborative work,Data privacy,Internet of Things,Contracts,Task analysis
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