In today’s episode, we discuss three pitfalls commonly seen when applying machine learning to cybersecurity.
- failing to understand how the results will be used by a security analyst
- temporal intermixing
- 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.