Securing SageMaker applications
As ML applications become integral to business operations, securing AWS SageMaker applications is paramount to safeguard sensitive data, maintain regulatory compliance, and prevent unauthorized access. In this section, you will first dive into the reasons for securing SageMaker applications and then explore different strategies to achieve security:
- Reasons to secure SageMaker applications
- Data protection: ML models trained on sensitive data, such as customer information or financial records, pose a significant security risk if not adequately protected. Securing SageMaker ensures that data confidentiality and integrity are maintained throughout the ML life cycle.
- Compliance requirements: Industries such as healthcare and finance are subject to stringent data protection regulations. Securing SageMaker helps organizations comply with standards such as the Health Insurance Portability and Accountability Act (HIPAA) or the General Data Protection Regulation...
