The sharing of genomic data holds great promise in advancing precision medicine and
providing personalized treatments and other types of interventions. However, these …

Machine learning and statistical techniques are powerful tools for analyzing large amounts
of medical and genomic data. On the other hand, ethical concerns and privacy regulations …

We suggest a method to construct a homomorphic encryption scheme for approximate
arithmetic. It supports an approximate addition and multiplication of encrypted messages …

This paper extends the leveled homomorphic encryption scheme for an approximate
arithmetic of Cheon et al.(ASIACRYPT 2017) to a fully homomorphic encryption, ie, we …

Fully Homomorphic Encryption (FHE) allows a third party to perform arbitrary computations
on encrypted data, learning neither the inputs nor the computation results. Hence, it provides …

In typical applications of homomorphic encryption, the first step consists for Alice of
encrypting some plaintext m under Bob's public key pk pk and of sending the ciphertext c …

Logistic regression is a powerful machine learning tool to classify data. When dealing with
sensitive data such as private or medical information, cares are necessary. In this paper, we …

Abstract In 2016, Albrecht, Bai and Ducas and independently Cheon, Jeong and Lee
presented very similar attacks to break the NTRU cryptosystem with larger modulus than in …

The problem we address is the following: how can a user employ a predictive model that is
held by a third party, without compromising private information. For example, a hospital may …

We introduce a CUDA GPU library to accelerate evaluations with homomorphic schemes
defined over polynomial rings enabled with a number of optimizations including algebraic …