AWS ML Security and Compliance

1. Which compliance standard applies to healthcare data in ML models?

PCI-DSS

HIPAA

FedRAMP

GDPR

2. Which encryption method protects model artifacts during SageMaker training job execution?

TLS encryption in transit and KMS at rest

Application-level encryption only

No encryption by default

AWS Signature Version 4 only

3. What is the purpose of data validation in ML pipelines regarding compliance?

Ensure data quality and detect privacy violations

Improve model performance only

Reduce training time

Increase endpoint throughput

4. How does enabling MFA Delete on S3 buckets enhance security?

Requires multi-factor authentication to delete objects

Encrypts bucket contents

Prevents public access

Enables versioning automatically

5. Which policy type restricts actions on S3 buckets containing training data?

Identity-based policy

Bucket policy

VPC endpoint policy

All of the above

6. What does S3 bucket versioning provide for ML model artifacts?

Protection against accidental deletion

Automatic encryption

Faster model access

Reduced storage costs

7. How can you ensure data privacy when sharing ML models across accounts?

Using cross-account IAM roles

Encrypting models with customer-managed KMS keys

Using both encryption and cross-account access

Sharing unencrypted models with restricted access

8. Which service monitors compliance with AWS security best practices?

AWS Config

AWS Security Hub

AWS Trusted Advisor

All of the above

9. What is the primary benefit of using AWS CloudTrail for ML auditing?

Track all API calls and user actions

Automatically fix security issues

Improve model accuracy

Reduce training time

10. How does SageMaker Network Isolation enhance security?

Prevents internet access during training

Encrypts model weights

Enables cross-account access

Increases GPU availability

11. Which AWS service encrypts data in transit and at rest for SageMaker notebooks by default?

AWS KMS

Amazon S3 Server-Side Encryption

SageMaker Encryption

AWS Secrets Manager

12. What does AWS Secrets Manager help protect in ML pipelines?

API keys and database credentials

Model source code

Training datasets

CloudFormation templates

13. How can you implement least privilege access for ML model endpoints?

Using resource-based policies

Using IAM identity policies

Using both IAM and resource policies

Using VPC security groups only

14. Which encryption option protects data in SageMaker EBS volumes?

S3 encryption

EBS encryption with KMS

TLS only

Application-level encryption

15. What is the role of IAM roles in SageMaker execution?

Grant services permission to access AWS resources

Encrypt model artifacts

Monitor model performance

Schedule training jobs

16. Which service provides centralized logging and monitoring for ML pipeline activities?

CloudWatch

CloudTrail

Config

Both A and B

17. What does AWS KMS customer master key (CMK) enable for ML workloads?

Automatic data validation

User-controlled encryption key management

Model versioning

Training job scheduling

18. How can you restrict access to SageMaker notebooks to specific IP addresses?

Using IAM policies only

Using security groups and NACLs

Using VPC and subnet configuration

All of the above

19. Which compliance framework requires encryption of personal data and restricts data transfers?

HIPAA

GDPR

SOC 2

PCI-DSS

20. What is the primary purpose of VPC endpoints in ML security?

Route traffic privately without internet exposure

Increase network bandwidth

Reduce SageMaker training costs

Enable cross-region replication

AWS ML Specialty ML Security and Compliance Quiz

1. Which compliance standard applies to healthcare data in ML models?

2.

What first name or nickname would you like us to use?

2. Which encryption method protects model artifacts during SageMaker training job execution?

3. What is the purpose of data validation in ML pipelines regarding compliance?

4. How does enabling MFA Delete on S3 buckets enhance security?

5. Which policy type restricts actions on S3 buckets containing training data?

6. What does S3 bucket versioning provide for ML model artifacts?

7. How can you ensure data privacy when sharing ML models across accounts?

8. Which service monitors compliance with AWS security best practices?

9. What is the primary benefit of using AWS CloudTrail for ML auditing?

10. How does SageMaker Network Isolation enhance security?

11. Which AWS service encrypts data in transit and at rest for SageMaker notebooks by default?

12. What does AWS Secrets Manager help protect in ML pipelines?

13. How can you implement least privilege access for ML model endpoints?

14. Which encryption option protects data in SageMaker EBS volumes?

15. What is the role of IAM roles in SageMaker execution?

16. Which service provides centralized logging and monitoring for ML pipeline activities?

17. What does AWS KMS customer master key (CMK) enable for ML workloads?

18. How can you restrict access to SageMaker notebooks to specific IP addresses?

19. Which compliance framework requires encryption of personal data and restricts data transfers?

20. What is the primary purpose of VPC endpoints in ML security?