Sphynx: A Deep Neural Network Design for Private Inference

Minsu Cho, Zahra Ghodsi, Brandon Reagen, Siddharth Garg, Chinmay Hegde

Research output: Contribution to journalArticlepeer-review


Private inference (PI) methods involving deep networks enable cryptographically secure machine learning but incur severe latency costs. We outline how neural architecture searches are used to design networks with fewer nonlinearities, enabling efficient PI.

Original languageEnglish (US)
Pages (from-to)22-34
Number of pages13
JournalIEEE Security and Privacy
Issue number5
StatePublished - 2022

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Law


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