Science News reports in its “Scientists put forth a smarter way to protect a smarter grid: Proliferation of programmable devices presents more gateways for cyberattack” article, that the more connected devices that are on the grid, the more vulnerable it becomes. This is not a new concern, but as the realization of smart grid devices and solutions get deployed, it becomes even more pressing. But team of experts from the US Department of Energy’s Pacific Northwest National Laboratory (PNNL) may have found a better way to manage this concern.

The team, led by data analyst for PNNL, Sumit Purohit, is turning the problem on its head. It’s difficult to imagine how to solve a security issue when there are tens of thousands of devices to be considered (and growing). Instead, what if the idea was to identify and prioritize the greatest cybersecurity threats at once and essentially create a blueprint of what needs to be fixed—and how quickly, all in real-time.

Science News quotes Purohit: “We’re putting forth a longer-term solution. What do you need to be looking at, not just today or tomorrow, but years down the road as the grid is changing?”

Leveraging real-world cyberattack data, Purohit and the PNNL team are creating unique models, coupled with Artificial Intelligence (AI) based on previous research conducted by the MITRE Corp. By using this framework, Purohit estimated that despite thousands of ways to attack utilities today, their research indicates that there are only about 100 ways that are most critical.

This could be revolutionary for how smart grid providers and cybersecurity experts collaborate on solving device security issues. While baked-in security is preferred, what is performed often leaves a lot to be desired. This is one method of approach that could move beyond the utility space and serve a host of markets that struggle with protecting critical systems due to security risks with intelligent devices.