UK Government Releases New AI Security Guidance

guest · Sep 5, 2022

By Phil Muncaster UK / EMEA News Reporter, Infosecurity Magazine - September 2, 2022

The UK’s leading security agency has released new guidance designed to help developers and others root out and fix vulnerabilities in machine learning (ML) systems.

GCHQ’s National Cyber Security Centre (NCSC) put together its Principles for the security of machine learning for any organization looking to mitigate possible adversarial machine learning (AML).
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AML attacks exploit the unique characteristics of ML or AI systems to achieve various goals. AML has become a more pressing concern as the technology finds its way into an increasingly critical range of systems, underpinning healthcare, finance, national security and more.

“At its foundation, software security relies on understanding how a component or system works. This allows a system owner to test for and assess vulnerabilities, which can then be mitigated or accepted,” explained NCSC data science research lead, Kate S.
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The new principles will help any entity “involved in the development, deployment or decommissioning of a system containing ML.” They aim to address several key weaknesses in ML systems, including: [...]

“In the NCSC, we recognize the massive benefits that good data science and ML can bring to society, not least in cybersecurity itself,” Kate S concluded. “We want to make sure those benefits are realized, safely and securely.”
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NCSC: Principles for the security of machine learning

Introduction to the principles
Alongside 'traditional' cyber attacks, the use of artificial intelligence (AI) and machine learning (ML) leaves systems vulnerable to new types of attack that exploit underlying information processing algorithms and workflows.

All aspects of an AI or ML system’s security are potentially vulnerable, and compromises of system confidentiality, integrity and availability have all been previously observed. Without properly understanding and mitigating these vulnerabilities, system designers can't assure stakeholders, and ultimately users, that an AI system is safe and secure.
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NCSC: Introducing our new machine learning security principles

Why the security of artificial intelligence (AI) and machine learning (ML) is important, how it's different to standard cyber security, and why the NCSC has developed specific security principles.
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