Amidst an era of evolving cyber-threats, legacy security approaches are being replaced by applications of machine learning and AI. While machine learning has the power to transform cyber defense, the challenge of getting it to work at scale, in a variety of dynamic data environments, without human intervention, is not trivial.
Download this whitepaper to learn more about:
- The different types of machine learning in the context of cyber security, including supervised, unsupervised, and deep learning
- Why supervised machine learning alone is insufficient for detecting subtle, novel threats
- How effectively implementing machine learning can proactively defend against a new era of threat