At its recent OpenWorld 2017 conference, Oracle kicked off a multi-pronged effort that promises to employ machine learning algorithms and other artificial intelligence (AI) technologies to address data security once and for all. The first of those efforts is centered around a forthcoming managed instance of an autonomous Oracle 18c database due out next year. That offering promises to eliminate the human errors that so often wind up leading to data being improperly accessed.
Armed with those capabilities, the company also launched its Identity Security Operations Center (SOC) portfolio of managed cloud services through which it plans to also employ machine learning and AI technologies to forecast, reduce, detect and automatically resolve cybersecurity threats.
Finally, the company unveiled an updated Oracle Management Cloud, which adds its eponymous Application Performance Monitoring and Infrastructure Monitoring Cloud Services to the core cloud service in addition to new Oracle Cloud Orchestration Service. Most significantly from a security perspective, the company has also enhanced its Log Analytics Cloud Service to enable organizations to monitor, aggregate and analyze both security and operational logs. Armed with that log data, it believes Oracle Management Cloud is an effective alternative to legacy security information event management (SIEM) platforms such as Splunk or the ArcSight platform now owned by Micro Focus.
While the autonomous database is squarely focused on securing data once it’s stored in an Oracle database, Oracle Identity SOC and Oracle Management Cloud are designed to employed across any application and infrastructure on-premises or deployed in a public cloud, says Dan Koloski, vice president of product management and business development for Oracle. Given the amount of data the company can collect and apply algorithms against, Koloski says it’s simply not possible for any internal IT organization to deliver an equivalent security and management capability on its own.
Rather the focusing solely on trying to secure applications, Koloski says, the Oracle initiatives are aimed at the entire stack, including the data being accessed by an application. If the data itself is secured, the degree to which an application is compromised becomes less relevant. The initiatives are significant from a DevSecOps perspective because too much money is being spent on security technologies that would not be required if data was secure in the first place, he says. Oracle uniquely has the resources and expertise needed to accomplish that goal using algorithms in the cloud to essentially combat the algorithms now being used by cybercriminals and nation states to compromise IT security, he adds.
Naturally, not every IT professional is going to agree on the degree to which Oracle can resolve all cybersecurity issues. But it is making clear that algorithms and other AI technologies will be a fundamental part of the IT security equation. As such, any approach to DevSecOps going forward won’t need to distinguish between what security tasks and functions in the future should be best left to a machine versus IT security professional and application developers.