• Content Type

Frameworks and principles

Principles for the security of machine learning


These principles aim to be wide reaching and applicable to anyone developing, deploying or operating a system with a machine learning (ML) component. They are not a comprehensive assurance framework to grade a system or workflow, and do not provide a checklist. Instead, they provide context and structure to help scientists, engineers, decision makers and risk owners make educated decisions about system design and development processes, helping to assess the specific threats to a system.

This content is available under the Open Government Licence v3.0

Key Information

Jurisdiction: UK - UK-wide

Name of organisation: National Cyber Security Centre

Date published: August 2022

License: Crown Copyright 2022


Domain: Horizontal

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