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Question 199 - MLS-C01 discussion

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A machine learning specialist is developing a proof of concept for government users whose primary concern is security. The specialist is using Amazon SageMaker to train a convolutional neural network (CNN) model for a photo classifier application. The specialist wants to protect the data so that it cannot be accessed and transferred to a remote host by malicious code accidentally installed on the training container.

Which action will provide the MOST secure protection?

A.
Remove Amazon S3 access permissions from the SageMaker execution role.
Answers
A.
Remove Amazon S3 access permissions from the SageMaker execution role.
B.
Encrypt the weights of the CNN model.
Answers
B.
Encrypt the weights of the CNN model.
C.
Encrypt the training and validation dataset.
Answers
C.
Encrypt the training and validation dataset.
D.
Enable network isolation for training jobs.
Answers
D.
Enable network isolation for training jobs.
Suggested answer: D

Explanation:

The most secure action to protect the data from being accessed and transferred to a remote host by malicious code accidentally installed on the training container is to enable network isolation for training jobs. Network isolation is a feature that allows you to run training and inference containers in internet-free mode, which blocks any outbound network calls from the containers, even to other AWS services such as Amazon S3. Additionally, no AWS credentials are made available to the container runtime environment. This way, you can prevent unauthorized access to your data and resources by malicious code or users. You can enable network isolation by setting the EnableNetworkIsolation parameter to True when you call CreateTrainingJob, CreateHyperParameterTuningJob, or CreateModel.

References:

Run Training and Inference Containers in Internet-Free Mode - Amazon SageMaker

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asked 16/09/2024
Hicham Jellab
44 questions
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