The advent of federated learning (FL) has sparked a new paradigm of parallel and
confidential decentralized machine learning (ML) with the potential of utilizing the …

The success of machine learning (ML) techniques in the formerly difficult areas of data
analysis and pattern extraction has led to their widespread incorporation into various …

Privacy protection is an essential part of information security. The use of shared resources
demands more privacy and security protection, especially in cloud computing environments …

The General Data Protection Regulation (GDPR) in the European Union contains directions
on how user data may be collected, stored, and when it must be deleted. As similar …

The success of current Large-Language Models (LLMs) hinges on extensive training data
that is collected and stored centrally, called Centralized Learning (CL). However, such a …

Intel has recently offered third-party attestation services, called Data Center Attestation
Primitives (DCAP), for a data center to create its own attestation infrastructure. These …

Blockchain technology and Artificial Intelligence (AI) have emerged as transformative forces
in their respective domains. This paper explores synergies and challenges between these …

The recent advent of various forms of Federated Knowledge Distillation (FD) paves the way
for a new generation of robust and communication-efficient Federated Learning (FL), where …

The development and application of artificial intelligence (AI) technology has raised many
concerns about privacy violations in the public. Thus, privacy-preserving computation …

Users can improve the security of remote communications by using Trusted Execution
Environments (TEEs) to protect against direct introspection and tampering of sensitive data …