Aug. 16, 2022, 1:13 a.m. | John Chiang

cs.CV updates on arXiv.org arxiv.org

In this work, we present a novel matrix-encoding method that is particularly
convenient for neural networks to make predictions in a privacy-preserving
manner using homomorphic encryption. Based on this encoding method, we
implement a convolutional neural network for handwritten image classification
over encryption. For two matrices $A$ and $B$ to perform homomorphic
multiplication, the main idea behind it, in a simple version, is to encrypt
matrix $A$ and the transpose of matrix $B$ into two ciphertexts respectively.
With additional operations, …

arxiv encoding inference networks neural networks privacy

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Data Engineer

@ Parker | New York City

Sr. Data Analyst | Home Solutions

@ Three Ships | Raleigh or Charlotte, NC