Data privacy concerns are increasing significantly in the context of the Internet of Things,
cloud services, edge computing, artificial intelligence applications, and other applications …

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

We unify the state-of-the-art bootstrapping algorithms for BGV and BFV in a single
framework and show that both schemes can be bootstrapped with identical complexity. This …

Amortized bootstrapping offers a way to refresh multiple ciphertexts of a fully homomorphic
encryption scheme in parallel more efficiently than refreshing a single ciphertext at a time …

BGV and BFV are among the most widely used fully homomorphic encryption (FHE)
schemes, supporting evaluations over a finite field. To evaluate a circuit with arbitrary depth …

Protocols for secure multi-party computation (MPC) supporting mixed-mode computation
have found a lot of applications in recent years due to their flexibility in representing the …

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 cryptosystem that allows the secure processing of
encrypted data. One of the most popular HE schemes is the Brakerski-Fan-Vercauteren …

Biometric data stored in automated recognition systems are at risk of attacks. This is
particularly true for large-scale biometric identification systems, where the reference …

Homomorphic encryption (HE) is a privacy-preserving computation technique that enables
computation on encrypted data. Today, the potential of HE remains largely unrealized as it is …