Amazon Web Services has launched a new security service that uses machine learning to help customers prevent data loss by automatically discovering, classifying, and protecting sensitive data in AWS.

Known as Amazon Macie, the service recognises sensitive data such as personally identifiable information (PII) or intellectual property, and provides customers with dashboards and alerts that give visibility into how this data is being accessed or moved.

The fully managed service continuously monitors data access activity for anomalies, and generates detailed alerts when it detects risk of unauthorised access or inadvertent data leaks.

Macie is designed to help organisations better control a growing volume of data. It automates labor-intensive processes, using machine learning to better understand where an organisation’s sensitive information is located and how it’s typically accessed, including user authentication, locations, and times of access.

“When a customer has a significant amount of content stored in Amazon S3, identifying and classifying all of the potentially sensitive data can feel a bit like finding needles in a very large haystack — especially with monitoring tools that aren’t smart enough to effectively automate what is now a very manual process,” said Stephen Schmidt, Chief Information Security Officer, Amazon Web Services.

“Amazon Macie approaches information security in a more intelligent way. By using machine learning to understand the content and user behaviour of each organisation, Amazon Macie can cut through huge volumes of data with better visibility and more accurate alerts, allowing customers to focus on securing their sensitive information instead of wasting time trying to find it.”

AWS customer Netflix is using the service to secure its customers’ PII.

“The security of our customers’ data is a top priority for Netflix, and we’ve invested substantial resources to build tools that protect sensitive information against unauthorised access or leaks,” said Patrick Kelley, Senior Cloud Security Engineer, Netflix.

“Since we started using Amazon Macie, we’ve found that it is flexible enough to solve a range challenges that would have previously required us to write custom code or build internal tools, such as securing PII and alerting us to access anomalies, helping us move fast with confidence.”

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