Serdab: An IoT Framework for Partitioning Neural Networks Computation across Multiple Enclaves

@article{Elgamal2020SerdabAI,
  title={Serdab: An IoT Framework for Partitioning Neural Networks Computation across Multiple Enclaves},
  author={Tarek Elgamal and Klara Nahrstedt},
  journal={2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID)},
  year={2020},
  pages={519-528}
}
  • Tarek Elgamal, K. Nahrstedt
  • Published 1 May 2020
  • Computer Science
  • 2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID)
Recent advances in Deep Neural Networks (DNN) and Edge Computing have made it possible to automatically analyze streams of videos from home/security cameras over hierarchical clusters that include edge devices, close to the video source, as well as remote cloud compute resources. However, preserving the privacy and confidentiality of users' sensitive data as it passes through different devices remains a concern to most users. Private user data is subject to attacks by malicious attackers or… Expand
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