AWS brings Amazon Macie into the spotlight
Utilising machine learning to monitor customer data, the new security service can help curb unauthorised access and data loss
Amazon Web Services (AWS) has unveiled a new security service aptly named Amazon Macie, which utilises machines learning to help minimise data loss and unauthorised access.
The new managed service recognises of sensitive data as personally identifiable information (PII), and in addition to classifying the information, the platform grants improved visibility via a dashboard, which displays how the data is utilised.
Amazon Macie is also able to generate alerts on anomalies associated with data access and can even store data in Amazon Simple Storage Service (Amazon S3).
Stephen Schmidt, chief information security officer, Amazon Web Services, commented: "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."
He added: "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."
Accessible via the AWS management Console, Amazon Macie's automated processes utilise machines learning to improve how sensitive information is located and accessed. Users in turn will be able to define and personalise automated remediation actions.
The latter includes the ability to reset access control lists, as well as engage password reset policies.
Patrick Kelley, senior cloud security engineer, Netflix, said: "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.
"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."