The latest quantum computers have the ability to solve incredibly complex classical
cryptography equations particularly to decode the secret encrypted keys and making the …

Blockchains have gained substantial attention from academia and industry for their ability to
facilitate decentralized trust and communications. However, the rapid progress of quantum …

As an emerging training model with neural networks, federated learning has received
widespread attention due to its ability to update parameters without collecting users' raw …

The main bottleneck affecting the efficiency of all known fully homomorphic encryption (FHE)
schemes is Gentry's bootstrapping procedure, which is required to refresh noisy ciphertexts …

Private Set Intersection (PSI) is a cryptographic technique that allows two parties to compute
the intersection of their sets without revealing anything except the intersection. We use fully …

Over the past years, the increasingly severe data island problem has spawned an emerging
distributed deep learning framework—federated learning, in which the global model can be …

HElib is a software library that implements homomorphic encryption (HE), specifically the
Brakerski-Gentry-Vaikuntanathan (BGV) scheme, focusing on effective use of the Smart …

Achieving fully homomorphic encryption was a longstanding open problem in cryptography
until it was resolved by Gentry in 2009. Soon after, several homomorphic encryption …

We extend the fully homomorphic encryption scheme over the integers of van Dijk et
al.(DGHV) into a batch fully homomorphic encryption scheme, ie to a scheme that supports …

Face recognition technology has demonstrated tremendous progress over the past few
years, primarily due to advances in representation learning. As we witness the widespread …