Hands-On Artificial Intelligence for Cybersecurity

Supervised learning

In the case of supervised learning, algorithm training is conducted using an input dataset, from which the type of output that we have to obtain is already known.

In practice, the algorithms must be trained to identify the relationships between the variables being trained, trying to optimize the learning parameters on the basis of the target variables (also called labels) that, as mentioned, are already known.

An example of a supervised learning algorithm is classification algorithms, which are particularly used in the field of cybersecurity for spam classification.

A spam filter is in fact trained by submitting an input dataset to the algorithm containing many examples of emails that have already been previously classified ...