In the cloud computing era, privacy protection is becoming pervasive in a broad range of
applications (eg, machine learning, data mining, etc). Fully Homomorphic Encryption (FHE) …

Homomorphic encryption is an emerging form of encryption that provides the ability to
compute on encrypted data without ever decrypting them. Potential applications include …

Homomorphic encryption (HE) offers great capabilities that can solve a wide range of
privacy-preserving computing problems. This tool allows anyone to process encrypted data …

We present a multi-GPU design, implementation and performance evaluation of the Halevi-
Polyakov-Shoup (HPS) variant of the Fan-Vercauteren (FV) levelled Fully Homomorphic …

With the rise of lattice cryptography,(negacyclic) convolution has received increased
attention. Eg, the NTRU scheme internally employs cyclic polynomial multiplication, which is …

Privacy guarantees are still insufficient for outsourced data processing in the cloud. While
employing encryption is feasible for data at rest or in transit, it is not for computation without …

Lattice-based cryptography (LBC) has been established as a prominent research field, with
particular attention on post-quantum cryptography (PQC) and fully homomorphic encryption …

Recent works challenged the number-theoretic transform (NTT) as the most efficient method
for polynomial multiplication in GPU implementations of fully homomorphic encryption …

Fully Homomorphic Encryption (FHE) allows computations on encrypted data without
knowledge of the plaintext message and currently has been the focus of both academia and …

KyberKEM is one of the final round key encapsulation mechanisms in the NIST post-
quantum cryptography competition. Number theoretic transform (NTT), as the computing …