Today's security threats are evolving each day, with IT teams having to closely monitor everything from the data
CIOs can no longer ignore the high-profile attacks that continue to threaten
But how is this actually achievable, unless we are able to anticipate the small, but significant, changes that are happening on the network day-to-day?
We are asking human IT teams to constantly monitor the data being shared by incoming and existing devices, which can easily reach into the thousands for a large the threats. Because human teams can get tired and make mistakes (they are human), the most common approach is to make blanket rules and restrictions across the network to serve as a catch-all against new inbound threats. The problem here, is that very quickly the user experience suffers. Which in turn, can affect productivity, and even morale.
This is where machine learning
Augmenting, not replacing
With any luck, that last sentence will not have made your eyes roll. We should be moving past concerns about AI replacing human roles. The point about ML, in the context of security, is that it gives us an always-on, 24/7 tool that allows us to spot the type of threats and exploits that it would be difficult, or even impossible, to detect with human eyes.
The way many companies run IT security today leaves definite room for improvement. Either you are running it with such sensitive filters that it generates a mountain of false positives, meaning you can't see the wood for the trees. Or filters are turned down to a manageable level, leaving big gaps in your
With ML, there is an ability to detect minute changes in data that would likely slip through traditional
As soon as a device behaves in a way that strays outside of its
In the case of a serious event, the device will be quarantined from the rest of the network, to limit any potential damage that might have occurred. All because the machine is
With machine-led security continually learning, adjusting baselines and detecting new threat patterns, human teams are not usurped. They are enormously aided, by being alerted only to the issues that they really need to inspect. This automatic monitoring offers IT
How security impacts the workplace
The tasks of human security workers may well change as the world of ML, building to full AI, begins to accelerate. But we should never fear change. Especially when the likely new roles carry even wider business relevance. The promise of ML is there, but it still needs highly skilled teams to build it into the core of the network, re-apply it to other business areas, and proactively monitor it for new insights.
We're faced by intelligent threats, targeting valuable user data, across a network that has more