Thought Leaders in Cyber Security: Mark Jaffe, CEO of Prelert (Part 6)

Sramana Mitra: I got it. Let’s actually take this forward. Now, I’m going to ask you to go up to that 30,000-foot level and talk to me about the application of artificial intelligence into the field of cyber security. In more general terms, what are some of the things that you’re seeing? Who’s doing what? What else can be done? What are other open problems that can be solved in this mode?

I was at a talk last night on artificial intelligence and startup opportunities in AI was advertised. Everything was discussed except for startup opportunities in artificial intelligence. It was not well moderated. Part of it is because it’s complex. I think the person moderating couldn’t really get to the heart of things. I do believe that security is an area where artificial intelligence is having a direct impact right now.

Mark Jaffe: It is. I think what’s interesting is that the state of the industry is such that, today, the best practices in machine learning and the advance thinkers in machine learning are building these supervised models. They’re cranking out more and more use cases. I think what we’ll see over time is, if customers don’t have to write new models per use case and they can use a platform to do that, they’ll do that. I think Prelert customers are the proof of this. That’s why we’re growing. Right now, we’re the only company doing that. I think there will be more. Just because we were able to crack the code on this unsupervised machine learning approach doesn’t mean others won’t try. It’s something that most folks didn’t believe was doable. It’s a little more advanced than most have tried. It’s a hard problem to solve.

It will make it easier for them to leverage the machine learning more rapidly. It’s all about time to deployment of these technologies. There are so many vectors of attack for which the fingerprints exist in so many different logs. Our customers are continuously expanding on their deployment of use cases. I think that will be the trend. Customers will be adopting machine learning approaches. When they do, it will be a focus on expanding the number of use cases.

You talked about where the opportunities for entrepreneurs are. I think there are a ton of opportunities out there. There are billions of dollars being spent on more traditional approaches. It’s good to have them, but they’re not solving the real problem. This is a real problem and it’s a problem that we got to solve. The opportunities are not only in driving change in organizations to centralize and aggregate data, but also to make that data available for analysis, to deploy both the data aggregation and the data analysis. We’re talking about the machine learning approach and leveraging that approach to build initiatives around developing and deploying new use cases.

Ultimately, there will be more time spent, not just chasing after false positives, but instead with organizations solving real problems. Our customers spend more time investigating real issues and solving real problems more rapidly than wasting time chasing ghosts, if you will.

Sramana Mitra: Over time, what you need to do in specific use cases becomes more widely available and can be programmed more directly into these machine learning systems. You find these use cases. The heuristic generation can also become more automated.

Mark Jaffe: Yes. Customers who say, “That worked really well on data exfiltration. I want to use those same approaches to find rare internal malware either laterally inside my network or from the outside in to my network.” That helps both the extension of the technology and the driving of use cases.

Sramana Mitra: Great! Thank you so much for your time.

This segment is part 6 in the series : Thought Leaders in Cyber Security: Mark Jaffe, CEO of Prelert
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