13 — Implement Data Security and Privacy Controls

13 — Implement Data Security and Privacy Controls

Module Introduction

• Introduction
• Defense-in-Depth for AI Strategy

Defense-in-depth

• Introduction
• Seven layers of security protection
• Architect defense-in-depth security for generative AI applications

Vpc Endpoints For Private Network Communications

• Introduction
• Benefits of using VPC endpoints for private network communications
• More on the benefits
• Endpoint security best practices resources

Secure Data Access Patterns With Iam Policies To Protect Ai Environments

• Introduction
• Benefits of securing data access patterns with IAM

Secure Enterprise Genai Applications Based On User Roles

• Introduction
• Securing Enterprise GenAI Applications
• Identity Federation
• Role-based access controls (RBAC)
• Secure API Access frameworks
• A few key takeaways:

Aws Lake Formation For Granular Data Access

• Introduction
• Understanding AWS Lake Formation for AI data governance
• Granular access control capabilities
• Integrating Lake Formation with AI services
• Fine-grained permission management
• Monitoring and compliance with Lake Formation
• Best practices for AI data governance

Monitor Data Access With Amazon Cloudwatch

• Introduction
• CloudWatch for monitoring data access
• CloudWatch Logs for AI security monitoring
• CloudWatch Logs Insights for analyzing AI application logs
• CloudWatch anomaly detection to identify unusual access patterns
• Best practices for AI security monitoring

Amazon Bedrock Native Data Privacy Features

• Introduction
• Amazon Bedrock Native Data Privacy
• Encryption and data protection capabilities
• Amazon Bedrock AgentCore
• Amazon Nova Models
• Best practices for using Bedrock native privacy features

Securing Pii Across Internal And External Ai Environments

• Introduction
• The challenges in AI environments
• Amazon Bedrock Guardrails for PII output filtering
• Amazon Comprehend
• Amazon Macie
• Implementing comprehensive PII protection architectures
• Amazon Nova models

Data Masking Techniques For Ai Systems

• Introduction
• Understanding data masking fundamentals for AI systems
• Anonymization strategies for AI data protection
• Pseudonymization techniques for AI data protection
• Masking techniques for vector embeddings in Amazon S3 Vectors

Data Retention Policies To Protect Sensitive Information In Fm Interactions

• Introduction
• Understanding data lifecycle management for AI applications
• Using Amazon S3
• Vector data retention considerations for S3 Vectors

Module Summary

• Recap and next steps
• Resources