Data providers are concerned about data privacy when a third party handles their data. A
typical example is cloud computing. In such cases, homomorphic encryption can be used to …

Fully homomorphic encryption (FHE) can utilize GPUs to accelerate arbitrary operations
directly on encrypted data without decryption. Functions like bootstrapping which refresh …

Homomorphic encryption is a tool that enables computation on encrypted data and thus has
applications in privacy-preserving cloud computing. Though conceptually amazing …

Recent expansions of cloud computing have been growing at a phenomenal rate. Security
and privacy issues have become a considerable issue while the applications of big data are …

Homomorphic encryption (HE) offers a promising solution for maintaining data privacy even
during calculation, as it allows for the evaluation of ciphertexts. Several HE libraries have …

With the burgeoning demands for cloud computing in various fields followed by the rising
attention to sensitive data exposure, Fully Homomorphic Encryption (FHE) is gaining …

Homomorphic Encryption (HE) is a promising solution to the increasing concerns of privacy
in machine learning. But HE-based CNN inference remains impractically slow. Pruning can …

Cloud computing has emerged as a prominent paradigm for the efficient storage and
processing of large volumes of data. However, the security of sensitive information remains …

Computing on encrypted data is a promising approach to reduce data security and privacy
risks, with homomorphic encryption serving as a facilitator in achieving this goal. In this work …

A hot topic in current cloud security research, homomorphic encryption is a recently
introduced technique allowing computation to take place on encrypted data. This work …