Security News > 2020 > December > Why stateful machine learning could help cybersecurity efforts
"Despite thousands of cybersecurity products, data breaches are at an all-time high," writes Bishop in his sponsored VentureBeat article To protect people, we need a different type of machine learning.
It has the ability to look at historical data and calculate important features by aggregating all of the relevant data points which are then passed to the machine learning model.
It may not be trivial, but stateful machine learning, according to Bishop, is the only way to protect employees and the sensitive data they access.
"And it happens more often than you might think. In organizations with over 10,000 workers, employees collectively send around 130 emails a week to the wrong person. That's over 7,000 data breaches a year." That's enough of a reason for Bishop to use securing email as an example of how stateful machine learning can be of help.
"Six months ago, the stateful model might have predicted that a 'Project Update' email to Eva looked normal," writes Bishop.