On May 22, the National Security Agency (NSA), the Cybersecurity and Infrastructure Security Agency (CISA), and international partners released new guidance to help organizations secure data used in artificial intelligence (AI) and machine learning (ML) systems. The document addresses key risks to data integrity across all phases of the AI lifecycle—from development and deployment to ongoing use.
The guidance highlights three critical areas of concern: the security of the data supply chain, the threat of maliciously modified or “poisoned” data, and the challenge of data drift—when data gradually changes in ways that degrade AI system performance. To counter these risks, it outlines best practices such as sourcing trusted data sets, using encryption and immutability tools, and applying digital signatures to track and validate changes to AI systems and their data.
“This crucial reference guide, compiled by the world’s leading government AI experts, is a must-read for health care leaders involved in the governance, development, or deployment of AI systems in their organizations,” said John Riggi, AHA’s national advisor for cybersecurity and risk. “It offers actionable methodologies to ensure data security and integrity throughout the entire AI lifecycle.”
For more information on this and other cybersecurity or risk-related topics, contact John Riggi at jriggi@aha.org. Access additional cyber and risk resources, including the latest threat intelligence, at aha.org/cybersecurity.
