Securing data in the AI supply chain - Atlantic Council
· Source: atlanticcouncil.org
In short
This report analyzes the complex data components within the AI supply chain, emphasizing the importance of securing various AI-related data elements beyond just training data or model weights. It proposes a framework categorizing seven key data components—training data, testing data, models, model architectures, model weights, APIs, and SDKs—and outlines three distinct approaches to assess and mitigate security risks: understanding data states, assessing threat actor profiles, and supplier risk management. The report concludes with recommendations urging AI stakeholders and policymakers to adopt comprehensive mapping and best practices from cybersecurity disciplines to address AI-specific risks while broadening the regulatory focus beyond singular data types.
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In the issue of week 36, 2025: AI-Driven Trade Intelligence and Security Redefine Global Supply Chains
Tags: supplychain, datasecurity, riskmanagement, governance, AImodels, cybersecurity