Corpus ID: 236493699

Secure Bayesian Federated Analytics for Privacy-Preserving Trend Detection

@article{Chaulwar2021SecureBF,
  title={Secure Bayesian Federated Analytics for Privacy-Preserving Trend Detection},
  author={Amit Chaulwar and Michael Huth},
  journal={ArXiv},
  year={2021},
  volume={abs/2107.13640}
}
Federated analytics has many applications in edge computing, its use can lead to better decision making for service provision, product development, and user experience. We propose a Bayesian approach to trend detection in which the probability of a keyword being trendy, given a dataset, is computed via Bayes’ Theorem; the probability of a dataset, given that a keyword is trendy, is computed through secure aggregation of such conditional probabilities over local datasets of users. We propose a… Expand

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