Oracle updates enterprise security service with machine learning

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Oracle added machine learning to its cloud management product to help better secure businesses against threats. The renamed Management and Security Cloud will take in data from on-premises and cloud infrastructure, then analyze them to help determine what might be a threat to a company’s data.

When the system determines that something fishy is going on, it can then automatically take steps to remediate the problem without human intervention. Customers can set up which steps they want a computer to handle automatically versus which ones just notify a human for further investigation.

All of this is based in the Oracle Cloud, but can ingest logs from a wide variety of sources that the enterprise tech giant doesn’t own or control. It’s all processed by pre-built machine learning models that Oracle has created to help protect customers.

It’s supposed to help prevent the next large-scale data breach for Oracle customers, like the Equifax hack or the breach that hit all of Yahoo’s users.

Oracle isn’t the first company to apply machine learning to security, of course. Microsoft recently announced Azure Advanced Threat Protection, which is designed to monitor a variety of data sources and help protect company data.

Splunk recently announced new features that make it easier for companies to apply their own models to logs that its eponymous software is analyzing. (That feature requires the assistance of data scientists, for what it’s worth.)

There are also a host of dedicated security companies like Darktrace that use machine learning to analyze what’s going on inside a company network. Cylance and Endgame are other dedicated businesses that focus on securing users’ endpoints using machine learning.

These capabilities build on existing ones in the Oracle Management and Security Cloud, like automated assessments for system configuration, IT analytics, and task reporting.

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