Tips For

Securing Al System Development

De: Cybersecurity and Infrastructure Security Agency

Narrado por: Tom Brooks

This document recommends guidelines for providers of any systems that use artificial intelligence (AI), whether those systems have been created from scratch or built on top of tools and services provided by others. Implementing these guidelines will help providers build AI systems that function as intended, are available when needed, and work without revealing sensitive data to unauthorized parties.

This document is aimed primarily at providers of AI systems who are using models hosted by an organization, or are using external application programming interfaces (APIs). We urge all stakeholders (including data scientists, developers, managers, decision-makers and risk owners) to listen to these guidelines to help them make informed decisions about the design, development, deployment and operation of their AI systems. About the guidelines AI systems have the potential to bring many benefits to society. However, for the opportunities of AI to be fully realised, it must be developed, deployed and operated in a secure and responsible way.

AI systems are subject to novel security vulnerabilities that need to be considered alongside standard cyber security threats. When the pace of development is high – as is the case with AI – security can often be a secondary consideration. Security must be a core requirement, not just in the development phase, but throughout the life cycle of the system. For this reason, the guidelines are broken down into four key areas within the AI system development life cycle: secure design, secure development, secure deployment, and secure operation and maintenance.

For each section we suggest considerations and mitigations that will help reduce the overall risk to an organisational AI system development process.

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©2023 Tom Brooks (P)2023 Tom Brooks