Security News > 2024 > July > Confidential AI: Enabling secure processing of sensitive data

Intel builds platforms and technologies that drive the convergence of AI and confidential computing, enabling customers to secure diverse AI workloads across the entire stack.

Confidential computing helps secure data while it is actively in-use inside the processor and memory; enabling encrypted data to be processed in memory while lowering the risk of exposing it to the rest of the system through use of a trusted execution environment.

Google Cloud confidential VMs are leveraging Intel Trust Domain Extensions technology on 4th Gen Intel Xeon Scalable CPUs so customers can run their AI models and algorithms in a TEE. Microsoft Azure Intel TDX-based confidential virtual machines are being powered by 4th Gen Intel Xeon Scalable processors to enable organizations to bring confidential workloads to the cloud without code changes to applications.

These services help customers who want to deploy confidentiality-preserving AI solutions that meet elevated security and compliance needs and enable a more unified, easy-to-deploy attestation solution for confidential AI. How do Intel's attestation services, such as Intel Tiber Trust Services, support the integrity and security of confidential AI deployments?

Intel's confidential AI technology combines proven solutions, such as Intel Trust Domain Extensions, Intel Software Guard Extensions and most recently, independent attestation by Intel Tiber Trust Services, to help protect AI data and models, and verify the authenticity of assets and the computing environments where those assets are used.

Intel's latest enhancements around Confidential AI utilize confidential computing principles and technologies to help protect data used to train LLMs, the output generated by these models and the proprietary models themselves while in use.

News URL

https://www.helpnetsecurity.com/2024/07/23/anand-pashupathy-intel-ai-data-protection/