Reviews: Partially Encrypted Deep Learning using Functional Encryption

Privacy in machine learning is being studied by many in the community due to its importance in many practical applications. Most studies use Homomorphic Encryptions or Secure Multi Party Computation to achieve privacy. This work uses Functional Encryption (FE) which is a different set of tools with different capabilities. I find this a great contribution since it may influence future research by demonstrating another plausible direction. Moreover, the authors present a new FE scheme, tailored to work well with machine learning workloads.