AAISM defines cryptographic tracking and verification as the best control for ensuring the integrity of training data. By applying hashing and verification methods, organizations can confirm that datasets remain unaltered and authentic throughout collection, storage, and processing. Collecting only necessary data, proper storage, or clear documentation all support governance and compliance, but they do not guarantee that the data has not been tampered with. Integrity is specifically ensured by cryptographic verification techniques.
[References:, AAISM Exam Content Outline – AI Risk Management (Data Integrity and Protection), AI Security Management Study Guide – Cryptographic Controls for Dataset Integrity, ]
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