ML Model Engineering AI Mitigations

An AI Bill of Materials (AI BOM) contains a full listing of artifacts and resources that were used in building the AI. The AI BOM can help mitigate supply chain risks and enable rapid response to reported vulnerabilities.

This can include maintaining dataset provenance, i.e. a detailed history of datasets used for AI applications. The history can include information about the dataset source as well as well as a complete record of any modifications.

Detect and block adversarial inputs or atypical queries that deviate from known benign behavior, exhibit behavior patterns observed in previous attacks or that come from potentially malicious IPs. Incorporate adversarial detection algorithms into the AI system prior to the AI model.

Establish access controls on internal model registries and limit internal access to production models. Limit access to training data only to approved users.

Apply deepfake detection algorithms against any untrusted or user-provided data, especially in impactful applications such as biometric verification, to block generated content.

Detectors may use a combination of approaches, including:

• AI models trained to differentiate between real and deepfake content.
• Identifying common inconsistencies in deepfake content, such as unnatural facial movements, audio mismatches, or pixel-level artifacts.
• Biometrics analysis, such blinking, eye movements, and microexpressions.