How AI Can Improve Network Security

Network managers are about to add a powerful new security technology to their toolbox: artificial intelligence.

AI promises the ability to analyze vast volumes of data without having a human around, says Shing-hon Lau, senior AI security researcher at Carnegie Mellon University's Software Engineering Institute, in an email interview. "AI can be targeted toward automating routine processes, freeing humans to analyze complex threats, or by trying to detect novel threats by rapidly analyzing large quantities of data."

The primary differentiator AI brings to the table is the ability to analyze large amounts of data and identify event patterns and correlations of that simply aren't feasible for a human, says Marc Herren, a director at technology advisory and research firm ISG, via email. "Over time, AI can recognize the start of a pattern and provide predictive alerts allowing network and security administrators to take corrective actions before an incident happens."

Why AI Is a Good Fit

Due to the fact that network security involves lots of data, AI is particularly well-suited for vital infrastructure protection. "When you have large amounts of data, you can have a high rate of false positives," says Sushila Nair, vice president and head of the North American cybersecurity practice at business advisory firm Capgemini, in an email interview.

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AI can also be used in network segmentation, isolating critical networks and decreasing an attack's the overall blast radius. "This approach is an important step in a zero-trust framework," Nair says. AI-powered micro-segmentation provides organizations with segmentation recommendations based on network traffic. It accomplishes this task by detecting overly permissive rules so that companies can segment based on application usage and asset criticality, which helps in limiting an attack's scope.

AI at the Edge

AI can analyze network traffic using deep packet inspection at a speed that human analysts simply can't match. "AI can crunch through the volumes of data rapidly to identify both external and internal threats," Nair says. "Since network data tends to be especially voluminous, AI is pivotal for this use case."

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