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The National Security Agency, Cybersecurity and Infrastructure Security Agency and international partners May 22 released guidance on securing data used for artificial intelligence and machine learning systems. The guidance outlines potential risks from data integrity issues in various stages of AI development and usage, and it provides best practices to secure AI-based system data. Additionally, the guidance examines three significant areas of data security risks in AI systems — the data supply chain, maliciously modified or “poisoned” data and data drift.  

“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 national advisor for cybersecurity and risk. “The guide discusses specific methodologies to help ensure data security and integrity throughout the AI system lifecycle. These include starting with sourcing reliable data sets and employing immutability and encryption tools, along with digital signatures, to validate and record any trusted changes to AI systems and data.” 
 
For more information on this or other cyber and risk issues, contact Riggi at jriggi@aha.org. For the latest cyber and risk resources and threat intelligence, visit aha.org/cybersecurity.