HEPack4ML '23

Proceedings of the 2023 Tutorial on Advanced HE Packing Methods with Applications to ML
Last Update : [26 November, 2023]

SESSION: HEPack4ML workshop

Tutorial-HEPack4ML '23: Advanced HE Packing Methods with Applications to ML
  • Ehud Aharoni
  • Nir Drucker
  • Hayim Shaul

Outsourcing computations over sensitive data to a third-party cloud environment should often rely on dedicated privacy-preserving solutions in order to adhere to privacy regulations such as the GDPR [ 7]. One solution that gained great attention is fully homomorphic encryption (FHE), a cryptographic method that allows performing different types of computation on encrypted data. Still, writing a non-interactive FHE code that evaluates complex functions is a task that is mostly left to experts. Otherwise, the resulted code may become very slow and even impractical. Tile tensor is a recent data structure that comes together with a dedicated language that aims to simplify the process of writing complex FHE programs. This tutorial introduces developers of security solutions without previous FHE background to the world of FHE programming through using tile tensors. It provides step-by-step guidelines for implementing complex operators such as matrix-multiplication and convolutions, and eventually guides the audience toward writing their own privacy-preserving convolutional neural network solution. The demonstrations in this tutorial use Python and the HElayers [1] library that implements tile tensors.

Demo: Rotating Wide Tensors with HElayers
  • Ehud Aharoni
  • Nir Drucker
  • Hayim Shaul

Tile tensor is a recent data structure accompanied by a rich language that fully homomorphic encryption (FHE) programmers can use to easily describe their solution. We demonstrate the tile tensor power by showing a technique that enables transparent handling of inputs larger than the selected ciphertext size. Specifically, we explain how to emulate large ciphertext operations using smaller ones without modifying the original packing design.