Domain 5 of 5

Security, Compliance and Governance for AI Solutions

Access control and encryption around a model, where training data came from and how you prove it, the standards an AI system is audited against, and the governance routine that keeps a deployed system accountable.

2
Concepts
~14%
Of the exam
9
Practice questions
Concepts in this domain
01Securing an AI systemAccess control, encryption and the shared responsibility model applied to machine learning, plus the attack surfaces that only exist because there is a model in the path.02AI governance and complianceThe standards an AI system gets audited against, what data governance means once a model is involved, and the review routine that keeps a deployed system accountable.
Try a question from this domain

A team using a fully managed foundation model service asks which security responsibilities are theirs under the AWS shared responsibility model. Which answer is correct?

  • AIdentity and access policy, encryption keys, what data is sent, and what the application does with the response.
  • BNone, because a managed service means AWS holds all responsibility for the workload.
  • CPatching the model hosts and configuring the underlying network.
  • DPhysical security of the data centres where inference runs.
9 questions on this domain.

One per page, with a worked explanation.

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