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Big data And AI Craziness Is Ruining Security Innovation

by Augusto Barros  |  April 11, 2018  |  Submit a Comment

I don’t care if you use Hadoop or grep+Perl scripts. If you can demonstrate enough performance to do what you claim you can do, that’s what matters to me from a backend point of view. Now, can you show me that your tool does what it should do better than your competitors?

There is a trend about the messages I’ve been hearing during vendor briefings over the past few months. They spend a lot of time talking about how great their architecture is, all those Hadoop stack components so beautifully integrated, showing how aligned to the latest data management, machine learning and analytics they are. They are proud of the stuff under the hood. But, very often, without verifiable claims on their effectiveness.

This is getting close to the insanity level. “We have AI”. “We are hadoop based”. “We do ML and Deep Learning”. It’s like the technology and techniques being used are the only thing to look for, and not the results! This may work to lure the VCs, but I cannot see how anyone would buy something that uses all this cool technology for…what exactly?

You see advanced analytics that provide “confidence levels” that do not change based on user feedback. Crazy visualizations that don’t tell you anything and could be easily replaced by a simple table view. “Deep Learning” for matching TI indicators to firewall logs. The list is endless.

My concern with this craziness is that vendors are mixing priorities here; they want to show they are using the latest techniques, but not worried about showing how effective they are. There are so many attempts to be the next “next-gen”, but not enough attempts to do help organizations solve their problems. This is killing innovation in security. I want to see how your tool makes threat detection 10x better, not that you can process 10x more data than your competitor.

There are cases where performance and capacity bottlenecks are the main pain point of an industry. Think SIEM before they started moving away from RDBMS, for example. But this is not always true. Now we see vendors happy to claim their products are based on Big Data technologies, but the use cases don’t require more than a few hundred megabytes of data stored. Stop that nonsense.

If you’re getting into this industry now, do so with a product that will work better than what organizations already have in place: findings more threats, faster and using less resources during detection and response. If your next-gen technology is not able to do so, it’s just a toy. And the message I hear from our clients is clear: We don’t want another toy, we want something that makes our lives easier.

 

Category: insights-and-philosophical  

Tags: machine-learning  trends  

Augusto Barros
Research VP
3 years at Gartner
21 years IT Industry

Augusto Barros is Research Director in the Gartner for Technical Professionals (GTP) Security and Risk Management group. Read Full Bio




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