3 Common Pitfalls When Applying Machine Learning to Cybersecurity

In today’s episode, we discuss three pitfalls commonly seen when applying machine learning to cybersecurity. 

These include:

  1. failing to understand how the results will be used by a security analyst
  2. temporal intermixing
  3. failing to adapt the output to common security workflows. 

Hope this video helps you go down the path – whether you are employing a new machine-learning based technology from a vendor, building your own machine learning capability in-house, or doing some combination of the two. 

3 Common Pitfalls When Applying Machine Learning to Cybersecurity