Combining the strengths of humans and machines for better security outcomes

The volume of threats and information that must be processed is greater than humans alone can manage. We need the speed of machines to process, adapt, and scale.

But we need humans as well to outmatch the wits and ingenuity of the human attackers on the other side of that code. We need teams of humans and machines, learning and informing each other—and working as one.

Driving the pace of innovation, McAfee is evolving beyond the standard forms of advanced analytics to adopt a multilayered approach known as human-machine teaming.

Machine learning applications in McAfee solutions consider:

  • Where the data will be gathered and computed
  • What raw data is needed and if sampling can be applied
  • The cost of bandwidth and latency to the customer
  • Where the periodic or continuous learning will occur
  •  Where, how, and when data will be stored
  • How often the model should be recalculated due to changing customer processes, metadata, or governance policies

Evolving machine learning for a better threat defense

Deep Learning and AI

Recent research highlights the need for machine learning for advanced detection capabilities. McAfee is evolving its machine learning technology to even more complex analytics called artificial intelligence (AI) and deep learning.

Multilayered Approach

Deep learning is an analytics approach based on machine learning that uses many layers of mathematical neurons—much like the human brain.

Humanlike Reasoning

Machine learning, deep learning, and artificial intelligence become mathematically more complex as the computation is more humanlike.

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