• Corpus ID: 218581566

Efficient Privacy Preserving Edge Computing Framework for Image Classification

@article{Fagbohungbe2020EfficientPP,
  title={Efficient Privacy Preserving Edge Computing Framework for Image Classification},
  author={Omobayode Fagbohungbe and Sheikh Rufsan Reza and Xishuang Dong and Lijun Qian},
  journal={ArXiv},
  year={2020},
  volume={abs/2005.04563}
}
In order to extract knowledge from the large data collected by edge devices, traditional cloud based approach that requires data upload may not be feasible due to communication bandwidth limitation as well as privacy and security concerns of end users. To address these challenges, a novel privacy preserving edge computing framework is proposed in this paper for image classification. Specifically, autoencoder will be trained unsupervised at each edge device individually, then the obtained latent… 
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