Corpus ID: 216144848

A Review of Privacy Preserving Federated Learning for Private IoT Analytics

  title={A Review of Privacy Preserving Federated Learning for Private IoT Analytics},
  author={Christopher Briggs and Zhong Fan and P{\'e}ter Andr{\'a}s},
The Internet-of-Things generates vast quantities of data, much of it attributable to an individual's activity and behaviour. Holding and processing such personal data in a central location presents a significant privacy risk to individuals (of being identified or of their sensitive data being leaked). However, analytics based on machine learning and in particular deep learning benefit greatly from large amounts of data to develop high performance predictive models. Traditionally, data and… Expand
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