Abstract: Federated learning enables training AI model without sharing of data, but requires protections such as homomorphic encryption to prevent reverse engineering of shared gradients, which incurs ...

Hecate (Homomorphic Encryption Compiler for Approximate TEnsor computation) is an optimizing compiler for the CKKS FHE scheme, built by Compiler Optimization Research Laboratory (Corelab) @ Yonsei ...

Privacy has become one of the most critical challenges in Web3. While blockchain technology enables transparency and trust, it also exposes user data in ways that ...

If you work or trade in the crypto space, there’s a good chance you’ve heard of Fully Homomorphic Encryption (FHE). You may even be familiar with some of the projects utilizing it to deliver onchain ...

“Fully Homomorphic Encryption (FHE) enables computation directly on encrypted data but incurs massive computational and memory overheads, often exceeding plaintext execution by several orders of ...

Artificial Intelligence (AI) is driving a new industrial revolution, transforming human workflows increasingly into digital tokens, i.e., tokenizing the entire world. However, this transformation ...

Abstract: Homomorphic Encryption (HE) enables computation on encrypted data, an essential capability for preserving privacy in cloud computing and Internet of Things (IoT) environments. While Fully ...

Fully Homomorphic Encryption (FHE) allows data to be processed without ever being decrypted. This means a third party can run meaningful computations on encrypted information without seeing the ...

Editor's note: The IAPP is policy neutral. We publish contributed opinion and analysis pieces to enable our members to hear a broad spectrum of views in our domains. Artificial intelligence depends on ...

Which feature or improvement would you like to request? A while ago, someone submitted the feature request to encrypt everything in the mailbox. While this is a good starting point, I have a different ...