Fully homomorphic encryption (FHE) is an emerging cryptographic technology that
guarantees the privacy of sensitive user data by enabling direct computations on encrypted …

Fully Homomorphic Encryption (FHE) is a key technology enabling privacy-preserving
computing. However, the fundamental challenge of FHE is its inefficiency, due primarily to …

Fully Homomorphic Encryption (FHE) enables the processing of encrypted data without
decrypting it. FHE has garnered significant attention over the past decade as it supports …

Convolutional neural network (CNN) inference using fully homomorphic encryption (FHE) is
a promising private inference (PI) solution due to the capability of FHE that enables …

Ring-Learning-with-Errors (RLWE) has emerged as the foundation of many important
techniques for improving security and privacy, including homomorphic encryption and post …

Homomorphic encryption (HE) is a promising technique for privacy-preserving
computations, especially the word-wise HE schemes that allow batching. However, the high …

Homomorphic encryption (HE)-based deep neural network (DNN) inference protects data
and model privacy but suffers from significant computation overhead. We observe …

Abstract Outsourcing Machine Learning (ML) tasks to cloud servers is a cost-effective
solution when dealing with distributed data. However, outsourcing these tasks to cloud …

A prevalent issue in the residue number system (RNS) variant of the Cheon-Kim-Kim-Song
(CKKS) homomorphic encryption (HE) scheme is the challenge of efficiently achieving high …

Fully homomorphic encryption (FHE) is a cryptographic technology capable of resolving
security and privacy problems in cloud computing by encrypting data in use. However, FHE …