Cloud computing is a long‐standing dream of computing as a utility, where users can store
their data remotely in the cloud to enjoy on‐demand services and high‐quality applications …

Homomorphic encryption (HE) enables the secure offloading of computations to the cloud by
providing computation on encrypted data (ciphertexts). HE is based on noisy encryption …

We introduce CryptGPU, a system for privacy-preserving machine learning that implements
all operations on the GPU (graphics processing unit). Just as GPUs played a pivotal role in …

Fully Homomorphic encryption (FHE) has been gaining in popularity as an emerging means
of enabling an unlimited number of operations in an encrypted message without decryption …

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

Machine learning algorithms have achieved remarkable results and are widely applied in a
variety of domains. These algorithms often rely on sensitive and private data such as …

Homomorphic Encryption (HE) is one of the most promising post-quantum cryptographic
schemes that enable privacy-preserving computation on servers. However, noise …

Fully Homomorphic Encryption (FHE) offers protection to private data on third-party cloud
servers by allowing computations on the data in encrypted form. To support general-purpose …

Deep Learning as a Service (DLaaS) stands as a promising solution for cloud-based
inference applications. In this setting, the cloud has a pre-learned model whereas the user …

As the application of deep learning continues to grow, so does the amount of data used to
make predictions. While traditionally big-data deep learning was constrained by computing …