Use an AI gateway to secure AI models and applications

How AI gateways work

AI gateways function similarly to API gateways, serving as a proxy between AI applications, AI models, users and other applications. These gateways can collate and assess all data inputs, routing only accurate data to the cloud.

Using authentication and encryption, AI gateways protect data as it moves between devices and across the network. This ensures that only authorized and authenticated devices can interact with AI systems and services. If an application needs to access an AI service, it sends a query to the gateway. Using either rules or an algorithm, the gateway then authenticates the query and passes it along to the relevant AI model or service.

AI gateways track communication between devices and networks in real time, expediting the discovery of questionable movements that could indicate a potential breach. They can also log requests and responses, establishing AI usage patterns.

How AI gateways secure AI models

AI gateways use multiple methods to protect AI models, large-language models and AI applications from cyber-risks.

Manage authentication and authorization

AI gateways work with identity and access management services to manage access to data. They restrict or permit access based on the user or device profile and network activity.

Implement data loss prevention policies

AI gateways apply DLP policies to restrict the transmission of sensitive and confidential information, thus helping stop data leaks within and outside the enterprise firewall. Gateways also interact with intrusion prevention systems to spot and deflect malicious traffic, for example, using deep packet inspection to identify a transmission from a threat actor.

Secure APIs connecting to AI tools

Because APIs offer a uniform interface, applications can communicate with multiple AI models using a standard API. AI gateways, such as Microsoft's AI gateway capability in Azure API Management, manage APIs connecting to AI tools and models to prevent accidental data exposure. This includes tracking authentication tokens across multiple applications and sharing the API key securely.

Improve compliance and governance efforts

By routing all traffic to and from AI models or tools, AI gateways enable organizations to comply with AI regulations within their industry. Specifically, AI gateways use traffic management, orchestration and security policy enforcement to meet compliance mandates such as HIPAA, GDPR and other privacy regulations, as well as AI regulations.

Other AI gateway capabilities

Beyond security, AI gateways offer performance benefits. For example, AI gateways can be set up to cache often-accessed data to improve efficiency and performance. They can also balance loads across service instances and measure response accuracy to identify potential service issues and then distribute workloads to improve uptime.

AI gateways are just one piece of AI security

AI gateways are an important protection element in securing AI models and applications, but not the sole AI security technology. An effective defense is a multilayered one that pulls together many resources to safeguard AI systems and their output. Additional security efforts include, for example, implementing an MLSecOps framework to establish AI guardrails, using proper data training and AI hardening to prevent data poisoning, adopting zero trust and following data security best practices.

Amy Larsen DeCarlo has covered the IT industry for more than 30 years, as a journalist, editor and analyst. As a principal analyst at GlobalData, she covers managed security and cloud services.