Data confidentiality is a central concern in modern computer systems and services, as
sensitive data from users and companies are being increasingly delegated to such systems …

Secure hardware enclaves have been widely used for protecting security-critical
applications in the cloud. However, existing enclave designs fail to meet the requirements of …

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 …

This paper addresses a key missing piece in the current ecosystem of decentralized
services and blockchain apps: the lack of decentralized, verifiable, and private search …

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 …

Abstract Information-sharing facilitates the coordination of supply chains and can be
essential for enterprises' survival. Studies have shown that supply chains benefit from the …

Federated learning (FL) relies on a central authority to oversee and aggregate model
updates contributed by multiple participating parties in the training process. This …

Pooling and sharing data increases and distributes its value. But since data cannot be
revoked once shared, scenarios that require controlled release of data for regulatory …

To support highly scalable and fine-grained computing paradigms such as microservices
and serverless computing better, modern hardware-assisted confidential computing …

Statistical analytics on encrypted data requires a fully-homomorphic encryption (FHE)
scheme. However, heavy computation overheads make FHE impractical. In this paper we …