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Privacy EngineeringeasyMultiple ChoiceObjective-mapped

CDPSE Privacy Engineering Practice Question

What is the primary privacy advantage of using 'On-Device Processing' for machine learning inference?

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

Reduction in data transfer of sensitive inputs

On-device processing keeps raw user data on the local device, preventing the need to transmit sensitive information to a central server.

Answer analysis

Option-by-option breakdown

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

  • Easier debugging of the model

    Why it's wrong here

    Debugging is typically harder in decentralized edge environments.

  • Reduction in data transfer of sensitive inputs

    Why this is correct

    By not sending the data to the cloud, the risk of interception or unauthorized storage is eliminated.

  • Faster cloud infrastructure scaling

    Why it's wrong here

    On-device processing reduces reliance on cloud infrastructure.

  • Improved model accuracy

    Why it's wrong here

    Accuracy is not necessarily improved by moving compute to the edge.

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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 CDPSE 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 CDPSE exam.