Which of the following controls MOST effectively helps to ensure an AI model is resilient against external threats?

The correct answer is D. AI model configuration testing. AI model configuration testing proactively verifies that the model is hardened and properly set up to withstand adversarial inputs, model poisoning, evasion attacks, and other external threats before they can be exploited. It ensures that security-relevant settings, input validat

AI Risk Management and Controls

Question

Options

AAI data set anonymization
BMonitoring of AI model developers
CMonitoring of AI access logs
DAI model configuration testing

How the community answered

(35 responses)

A
6% (2)
B
11% (4)
C
3% (1)
D
80% (28)

Explanation

AI model configuration testing proactively verifies that the model is hardened and properly set up to withstand adversarial inputs, model poisoning, evasion attacks, and other external threats before they can be exploited. It ensures that security-relevant settings, input validation, and guardrails are functioning as intended. Dataset anonymization (A) is a privacy control, not a resilience mechanism. Monitoring developers (B) addresses insider threats, not external ones. Monitoring access logs (C) is a detective control that identifies incidents after the fact, whereas configuration testing is preventive and directly targets the model's ability to resist external attacks.

Topics

#AI Security Controls#Model Resilience#External Threats#Configuration Testing

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