When evaluating AI/ML offerings, how do you decide which is best for you and your organization?

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Sr. Director, Security Engineering & Threat Management4 years ago

Probably one of the more difficult things, I find, is trying to keep up with all the tech, but also be pragmatic in the process. Because it's easy to go out and want to buy all the new cool stuff. But is it really realistic to try and implement and deploy all that, manage all that? That's the microservices conundrum. Someone just posted something recently... “I thought that moving to microservices was gonna make my job easier for everything. And now every time we have an outage, it's like murder mystery.” So it's interesting to kind of see the give and take that comes with that. A lot of offerings are all going to have things that are going to be more or less localized to what you're looking for.

Head of Information and Data Analytics in Software4 years ago

It's not just about deploying the tool, but focusing on the value part. This is generally missing in general IT, and it’s even worse when it comes to security. It's not just about the speed to insight, but focusing on the insight to action, how do you connect value, and is that going to be right for your stack? That's where the focus should be.

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Sr Director of Information Security and Compliance4 years ago

Something that we use to our advantage a lot of the time is… we find the data that we know is good, or the traffic that we know is normal, and we put it aside. And then we focus on what's left. We look at that and we try to figure out what is good and what's not. And we throw that out and we focus on what's left. Eventually we work ourselves down to a data set that's manageable, and then we can figure out what's really going on by looking at the big picture and saying, okay, forget all the noise, right. The noise is good. We've checked it. Let's figure out what we don't know. And that's where we find most of our issues. That's hard to do, but that's really how we do it with bigger data sets. You can't look at it all. You got to start saying, this is good. This is good. This is good…. Oh, what's this? And then work your way from there.