From the course: AWS Certified AI Practitioner (AIF-C01) Cert Prep

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Question breakdown, part 1

Question breakdown, part 1 - Amazon Web Services (AWS) Tutorial

From the course: AWS Certified AI Practitioner (AIF-C01) Cert Prep

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Question breakdown, part 1

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- Welcome. In this practice question, we have a scenario that involves healthcare AI data security. Let's go ahead and read the question. A company specializes in AI-driven healthcare analytics. The company handles sensitive patient data and it is facing significant pressure to ensure data privacy and security. One of the main concerns is how to secure the data during processing without exposing it to unauthorized parties. Which of the following techniques would be most effective for the company to implement? And we have four different choices. Federated learning, attribute-based access control, homomorphic encryption, or data anonymization. And so let's go ahead and take a look at our answer choices, starting with A, federated learning. Now, this is a privacy enhancing technique for training models across decentralized data sources without transferring sensitive data. However, the key concern in this specific scenario is how do we secure the data during the processing itself? So…

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