The 4-1-1 on SecOps and Machine Learning

by in Security

Hello, operator? The truth about machine learning, please.  

If you’ve ever wished for a live fact-checker during a conversation with a security vendor about machine learning or artificial intelligence (AI), well, you’re not alone. With all the commotion around AI and machine learning in the past few years, it’s no wonder so many folks are scratching their heads thinking, “What’s the real deal with machine learning, anyway?” 

The 4-1-1 on SecOps and Machine Learning.pngFor the Interset team, it’s particularly concerning to see the results of the cybersecurity industry’s collective ballyhoo around machine learning. Some people find themselves skeptical about the real power of machine learning, and some grasp at it with a vision of a silver bullet poised to solve all of their security operations woes. These types of attitudes make it difficult to achieve a successful deployment of machine learning in a security operations center (SOC). You have to understand the capabilities of the tool in your hand—its strengths and its limitations—in order to use it effectively. You wouldn’t have much luck chopping down a tree with a hammer, nor would it be productive to use a chainsaw to hang a picture frame. 

So, what really is the deal with machine learning in the SOC? The data scientists and cybersecurity experts behind Interset’s user and entity behavioral analytics (UEBA) have spent years tackling this exact topic. Today, Interset uses hundreds of machine learning to power its anomaly detection, helping SOC teams to spend less time on manual processes and more time on investigating real threats. An important ingredient to Interset’s success is our experts’ understanding of how to implement and operationalize machine learning in the most effective way. But you don’t need to take my word for it. I’ll let them explain it to you. 

In our new three-part video series, Interset experts share the ins and outs of machine learning in the SOC. In the first chapter, you’ll hear about the true power of machine learning for supercharging your security operations. The second chapter explores why it’s critical to start your implementation by identifying the security problems you’re trying to solve. And the final chapter shares a few key best practices to keep in mind before and during your implementation of machine learning technologies. 

Part 1: Speed Up Your SecOps

Part 2: Identify Your Use Cases

Part 3: Best Practices for Success

Learn how Micro Focus can protect your business by arming your SOC with powerful machine learning by visiting


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