Confidential Computing To Secure AI Workloads


Artificial Intelligence (AI), data analytics, and high-performance computing (HPC) are transforming industries such as healthcare, finance, and manufacturing. These workloads rely on distributed systems managing massive datasets with high reliability. As computational demand grows, so does the need for end-to-end data protection. Traditional security addresses Data at Rest (DAR) and Data in ... » read more

Lightweight, High-Performance CPU Extension for Protected Key Handles with CPU-Enforced Usage (CISPA, Ruhr Univ. Bochum)


A new technical paper titled "KeyVisor -- A Lightweight ISA Extension for Protected Key Handles with CPU-enforced Usage Policies" was published by researchers at CISPA Helmholtz Center for Information Security and Ruhr University Bochum. Abstract "The confidentiality of cryptographic keys is essential for the security of protection schemes used for communication, file encryption, and outsou... » read more

HECTOR-V: A Heterogeneous CPU Architecture for a Secure RISC-V Execution Environment


Summary "To ensure secure and trustworthy execution of applications, vendors frequently embed trusted execution environments into their systems. Here, applications are protected from adversaries, including a malicious operating system. TEEs are usually built by integrating protection mechanisms directly into the processor or by using dedicated external secure elements. However, both of these... » read more