Matthew Rosenquist explains how AI can scan for vulnerabilities across your infrastructure continuously. The biggest risk: if attackers compromise machine-to-machine communications, they could sabotage production lines and cause physical damage, not just steal data.
on the positive side, we can use AI for security more effectively too, you know. So it's not all downside. And I think we need to understand the risks and the upside can be— we can protect ourselves, we can deploy agents at points of vulnerability to, to, to scan what's going on. And that, that's probably where the best value is going to be, using AI as an intelligence network to see where our points of vulnerability are and how that changes. You know, if you bring some software in, it opens up a whole set of other things. How does that vector sort of opening up change what we're doing? And, and I think nowhere is that better illustrated in operations. You know, you've got machine-to-machine communication, which is, you know, you don't have the same people issues involved, but how do you, how do you make sure that there's no points of vulnerability there? I mean, if If somebody can get access to you messing up your production line, they can cause serious damage, way more than just a privacy leak.
The Future of Cybersecurity: How AI Is Exploiting Technical, Behavioral, and Process Vulnerabilities
