Скачать или смотреть Securing AI Data: Encryption, VPC Endpoints, and IAM Roles

Generative AI is transforming the way we work, but it also paints a giant target on your sensitive data. From data poisoning to model theft, the risks are real. So, how do you build a fortress around your AI models?

In this explainer, we break down the "Defense in Depth" strategy required to secure AI workloads in the cloud. We explore the recommendations from NIST and dive into the three critical layers of protection: Encryption, Networking, and Access Control.

In this video, you’ll learn:

The AI Data Problem: Why model data is uniquely vulnerable to attacks like poisoning and inversion.

Layer 1 (Encryption): Protecting data at rest, in transit, and crucially, in use via Confidential Computing (TEEs).

Layer 2 (Networking): How to use VPC Endpoints to keep your traffic off the public internet for compliance (HIPAA, PCI-DSS).

Layer 3 (Access): Implementing the Principle of Least Privilege using IAM user and service roles.

CHAPTERS: 0:00 - The AI Security Challenge 0:36 - NIST & Data Poisoning Risks 1:41 - Layer 1: Encryption & Confidential Computing 2:53 - Layer 2: Private Networking (VPC) 4:03 - Layer 3: IAM & Access Control 5:13 - The Big Picture: Defense in Depth

#AI #Cybersecurity #DataPrivacy #GenerativeAI #CloudSecurity #ConfidentialComputing