There has been a recent effort in applying differential privacy on memory access patterns to
enhance data privacy. This is called differential obliviousness. Differential obliviousness is a …

Most cloud service providers offer limited data privacy guarantees, discouraging clients from
using them for managing their sensitive data. Cloud providers may use servers with Trusted …

Many individuals and companies choose the public cloud as their data and IT infrastructure
platform. But remote accesses over the data inevitably bring the issue of trust. Despite strong …

Differential obliviousness (DO) is a privacy notion which guarantees that the access patterns
of a program satisfies differential privacy. Differential obliviousness was studied in a …

Combining Federated Learning (FL) with a Trusted Execution Environment (TEE) is a
promising approach for realizing privacy-preserving FL, which has garnered significant …

In cloud computing, remote accesses over the cloud data inevitably bring the issue of trust.
Despite strong encryption schemes, adversaries can still learn sensitive information from …

Differential obliviousness (DO) is a privacy notion which mandates that the access patterns
of a program satisfy differential privacy. Earlier works have shown that in numerous …

Secure collaborative analytics (SCA) enable the processing of analytical SQL queries
across multiple owners' data, even when direct data sharing is not feasible. Although …

In cloud databases, cloud computation over sensitive data uploaded by clients inevitably
causes concern about data security and privacy. Even when encryption primitives and …

Individuals and organizations are accumulating data at an unprecedented rate owing to the
advent of inexpensive cloud computing. Data owners are increasingly turning to secure and …