AI0-001 AI Security, Ethics and Governance Practice Question
A healthcare AI system misdiagnosed patients due to adversarial inputs. What security measure should be prioritized?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Implement adversarial training
(Implement adversarial training) is correct because adversarial training makes the model robust to input manipulation. Option A (Encrypt all patient data) protects data privacy but not model integrity. Option B (Use stronger authentication) is for access control. Option C (Regular software updates) is general maintenance and does not specifically address adversarial inputs.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
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Encrypt all patient data
Why it's wrong here
Encryption protects data at rest and in transit, but adversarial inputs are crafted to manipulate model inference, so ciphertext is decrypted before the model processes it. Encryption would be correct for securing stored patient records or network interception, not for detecting or hardening against malicious input perturbations.
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Use stronger authentication
Why it's wrong here
Stronger authentication verifies user identity at login and does nothing against crafted inputs submitted to a trained model. Authentication suits protecting access to systems and APIs, whereas adversarial misdiagnosis requires input validation, adversarial training or anomaly detection on inference data.
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Regular software updates
Why it's wrong here
Software updates patch known code vulnerabilities but do not alter a model's learned decision boundaries, so manipulated inputs still produce wrong diagnoses. Updates suit remediating exploitable software flaws; adversarial robustness instead needs adversarial training, input sanitisation or detection of out-of-distribution inference inputs.
- ✓
Implement adversarial training
Why this is correct
Adversarial training augments the training set with perturbed examples, hardening the model's decision boundaries against the malicious inputs that caused misdiagnosis. This directly satisfies the healthcare scenario's requirement to withstand adversarial manipulation, unlike filtering or monitoring, which detect but do not immunise the model.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI0-001 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI0-001 exam.