Episode 40 — Manage Sensitive Data Risks: PII, PHI, Secrets, and Proprietary Content (Domain 3)
The use of sensitive data in AI training and inference poses significant security and privacy risks that are central to Domain 3. This episode details the specific hazards of processing Personally Identifiable Information (PII), Protected Health Information (PHI), trade secrets, and proprietary intellectual property. For the AAIR exam, candidates must know how to implement technical mitigations such as data anonymization, differential privacy, and secure enclaves to protect this information. We discuss the risks of "memorization," where a model might inadvertently reveal sensitive training data in its outputs, and the importance of using data loss prevention (DLP) tools to monitor AI interactions. Best practices include conducting Data Protection Impact Assessments (DPIAs) before using sensitive data in any AI project. By managing these risks with precision, organizations can leverage the power of AI while remaining in compliance with strict global privacy regulations like GDPR and CCPA, ensuring that their most valuable data assets are never compromised. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
