Date Published: May 29, 2026
Comments Due:
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Author(s)
Michael Bartock (NIST), Murugiah Souppaya (NIST), Timothy Knoll (Intel)
Announcement
The National Cybersecurity Center of Excellence (NCCoE) invites public comments NIST Interagency Report (NIST IR) 8320E ipd (initial public draft), Hardware-Enabled Security: Confidential Computing of Data in Cloud Workloads. This is the latest in a series of reports on hardware-enabled security techniques and technologies.
Confidential computing addresses data security and privacy concerns for organizations that move sensitive workloads to the cloud. It is a critical advancement that enables the encryption of data while it is being processed in memory, extending encryption coverage to data in active use. As cloud adoption continues to grow, confidential computing will play a pivotal role in improving security and privacy in cloud environments.
IR 8320E describes an example approach to protecting data being acted upon by artificial intelligence workloads on cloud infrastructures so that the datasets are protected from malware, data theft, and other security-related vulnerabilities. This report is intended to be a blueprint that the general security community can use to validate and utilize the described implementation.
The public comment period for this draft is open through July 13, 2026. See the publication details for a copy of the draft and instructions for submitting comments. You can also contact the authors at [email protected].
Confidential computing addresses data security and privacy concerns for organizations that move sensitive workloads to the cloud. It is a critical advancement that enables the encryption of data both while it is being processed in memory and in active use. As cloud adoption continues to grow, confidential computing will play a pivotal role in improving security and privacy in cloud environments. This report describes an effective approach to protecting data being acted upon by artificial intelligence workloads on cloud infrastructures so that the datasets are protected from malware, data theft, and other security-related vulnerabilities.
Confidential computing addresses data security and privacy concerns for organizations that move sensitive workloads to the cloud. It is a critical advancement that enables the encryption of data both while it is being processed in memory and in active use. As cloud adoption continues to grow,...
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Confidential computing addresses data security and privacy concerns for organizations that move sensitive workloads to the cloud. It is a critical advancement that enables the encryption of data both while it is being processed in memory and in active use. As cloud adoption continues to grow, confidential computing will play a pivotal role in improving security and privacy in cloud environments. This report describes an effective approach to protecting data being acted upon by artificial intelligence workloads on cloud infrastructures so that the datasets are protected from malware, data theft, and other security-related vulnerabilities.
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Keywords
confidential computing; cryptographic key; hardware-enabled security; hardware security module (HSM); machine identity; machine identity management; trusted execution environment (TEE)
Control Families
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