Let’s talk about security and Generative AI. What happens to security when we use generative artificial intelligence? This is a question that is constantly repeated in conversations with customers, especially when thinking about developing solutions with confidential information of companies, such as customer financial data, personal information or processes, for example.
Generative AI, such as ChatGPT, is partly responsible for this questioning. Those who have used it know that its benefits are achieved thanks to its nature: learning from open data and from the data of the users who use it daily.
This feature can be insecure, and as such, no company should build or share classified information with tools that don’t guarantee the privacy and security of their data.
Amazon Web Services Generative AI:
The AWS Cloud offers Generative AI services that enable users to securely develop solutions with diverse use cases, with a focus on protecting customer data. To answer the initial question, it’s important to understand the AWS security background.
What is Amazon Bedrock?
It is AWS’s core Generative AI service. Amazon Bedrock is a fully managed service that offers several foundational generative AI models built by different vendors, with a set of capabilities to build fully customizable AI applications privately and securely. This service allows us to develop intelligent solutions that respond according to the needs, data and settings of each company.
In addition, this product applies the shared responsibility model, in which AWS is responsible for protecting the infrastructure where applications run, while users are responsible for configuring security and related services.
It is important to note that:
How does Generative AI work on AWS?
On AWS, generative AI models are provided by different vendors through a deployment account in each region, managed by the Amazon Bedrock team.
Providers do not have access to AWS accounts; the Amazon Bedrock team makes a copy of the inference and training software. As a result, suppliers do not have access to records or any customer information.
In short, the copy of the Generative AI model used only contains the trained software, not including the information with which it was trained. No additional information is generated for training by providers, as they do not have access to data or any other information outside of AWS.
When a generative AI solution is enabled with this service, one individual copy is generated in each AWS account, as well as one copy per region. This means that data is not stored in a common place; each customer has their own copy of Amazon Bedrock models.
In addition, AWS Generative AI encrypts information from sessions using an AWS-managed key, and all requests to the models’ API are made over a secure SSL connection.
You can even use AWS PrivateLink to create a private connection between your own VPC and Amazon Bedrock, without using an Internet access port.
Best Practices: Key Principle for Generative AI in your Company
Like any other Amazon Web Services service, you need to build an infrastructure with good security practices, such as:
In other words, an environment must be built under the best practices of the Amazon Web Services security pillar, since everything that is developed must comply with these guidelines, regardless of whether the Generative AI models are built and deployed safely.
Therefore, with the help of a specialized partner, a solution can be built in a highly secure environment.
Facts about Security and Generative AI:
All this in contrast to cases that are built with a service that must comply with regulations and standards, as is the case with Amazon Web Services.
See you in the Cloud!
As an AWS Advanced Partner and strategic business partner, we help organizations on their path to the future of cloud and generative AI. With a proven track record of success in cutting-edge technology implementations and through the expertise of our team of certified specialists, we facilitate enterprise digital transformation.
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