Addressing Security Challenges in Generative AI with AWS Marketplace

Introduction

In collaboration with leading enterprises, the rise of generative AI and its application across an ever-expanding set of business processes presents security and operational challenges that didn’t exist as recently as five years ago. As organizations adopt AI-driven technologies, they face increasing concerns about data privacy, security, and compliance. AWS Marketplace offers a comprehensive set of security products and services, including expert support, to address the needs of the generative AI-driven enterprise.

With security being a chief concern for organizations, we’ve compiled 10 frequently asked questions about generative AI security and how AWS tools can address them.

1. How do I apply consistent and responsible policies across all generative AI models?

A broad range of Amazon Web Services (AWS) tools, including guardrails for Amazon Bedrock, makes it possible to enforce policy compliance across the enterprise. Bedrock offers industry-leading safety features on top of native foundational model (FM) capabilities, helping customers block as much as 85% more harmful content.

2. How do I maintain consistent safety levels across complex, heterogeneous systems and applications?

Amazon Bedrock provides tools that allow enterprises to implement a uniform standard of safety across all their AI applications. With its built-in capabilities, you can filter out harmful content and restrict inappropriate topics in both AI inputs and outputs, helping mitigate legal, regulatory, and reputational risks.

3. Can I prevent harmful or inappropriate content in generative AI inputs and outputs?

Yes, Amazon Bedrock enables enterprises to filter and block harmful content effectively, protecting the organization from potential liability and ensuring compliance with various industry standards.

4. How do I avoid exposure of personally identifiable information (PII) in foundational models?

AWS features built-in capabilities to redact sensitive information, including PII, ensuring your enterprise data remains protected and preventing accidental data exposure through generative AI applications.

5. How do I ensure my enterprise data remains under my control?

Amazon Bedrock allows enterprises to create private copies of fine-tuned models, protecting against unauthorized data access and malicious usage. This ensures your AI models are controlled and secured within your organization, without the risk of data leaks.

6. How do I secure connectivity without internet exposure?

AWS PrivateLink provides private and secure connections without the need for internet exposure. This feature offers enhanced protection and reduces the attack surface for AI-powered applications by limiting external access points.

7. How do I prevent the use of my enterprise data by model providers?

Amazon Bedrock is designed to ensure that your enterprise data remains fully under your control. This means your data is not shared with model providers or used to improve the foundational models, protecting your organization’s intellectual property.

8. Do I have full control over the data used to customize foundation models?

AWS offers comprehensive encryption measures to protect data both in transit and at rest, ensuring that all data used to customize AI models is fully controlled by your organization.

9. How do I meet complex, rigorous, and evolving regulatory compliance requirements?

Amazon Bedrock is in scope for various regulatory frameworks, including the International Organization for Standardization (ISO), Health Insurance Portability and Accountability Act (HIPAA), and General Data Protection Regulation (GDPR). It ensures compliance with key industry-specific standards, allowing enterprises to meet even the most stringent regulatory requirements.

10. How can I monitor, log, and audit a generative AI environment?

AWS CloudWatch and AWS CloudTrail offer robust monitoring, logging, and auditing capabilities. These services help security teams identify, respond to, and report on potential security issues quickly and efficiently. Integration with over 70 AWS services also simplifies monitoring and ensures scalability as your generative AI environment grows.

Conclusion

Generative AI brings unprecedented potential, but it also comes with unique security challenges. By leveraging the advanced security tools and services available through AWS Marketplace, enterprises can implement robust safety measures, ensuring that they harness the power of AI while minimizing risk. Whether it’s maintaining data control, adhering to regulatory standards, or safeguarding sensitive information, AWS provides the expertise and technology needed to protect AI-driven environments.