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AAIA AI Governance And Risk Practice Question

An organization is using 'Federated Learning' to maintain data privacy while training models. What is the primary audit risk associated with this architecture?

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

Model inversion attacks targeting the central aggregator

In Federated Learning, local model updates (gradients) can potentially reveal information about the underlying training data, necessitating 'Differential Privacy' as a control.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Increased training latency

    Why it's wrong here

    This is a performance risk, not a fundamental security or governance risk.

  • Model inversion attacks targeting the central aggregator

    Why this is correct

    The aggregation of gradients can be exploited to reconstruct private training data.

  • Lack of access to training hardware

    Why it's wrong here

    Hardware access is a capacity planning issue, not an architectural risk.

  • Centralized data breaches

    Why it's wrong here

    Federated learning is designed to avoid centralizing data, reducing this specific risk.

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JA

Written and reviewed by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

Last reviewed August 2026 · checked against the official ISACA exam blueprint

This AAIA practice question is part of Courseiva's free ISACA 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 AAIA exam.