Legacy encryption systems depend on sharing a key (public or private) among the peers
involved in exchanging an encrypted message. However, this approach poses privacy …

It is unlikely that a hacker is able to compromise sensitive data that is stored in an encrypted
form. However, when data is to be processed, it has to be decrypted, becoming vulnerable to …

With the rapid increase in cloud computing, concerns surrounding data privacy, security, and
confidentiality also have been increased significantly. Not only cloud providers are …

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) …

Artificial intelligence (AI) shows potential to improve health care by leveraging data to build
models that can inform clinical workflows. However, access to large quantities of diverse …

With the development of the important solution for privacy computing, the explosion of data
size and computing intensity in Fully Homomorphic Encryption (FHE) has brought enormous …

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 …

Fully homomorphic encryption (FHE) allows arbitrary computation on encrypted data and
has great potential in privacy-preserving cloud computing and securely outsource …

Homomorphic encryption allows computation on encrypted data and makes it possible to
securely outsource computational tasks to untrusted environments. However, all proposed …

In this paper we report on our advances designing and implementing an FPGA-based
computation accelerator as part of a Homomorphic Encryption Processing Unit (HEPU) co …