Hands-On Artificial Intelligence for Cybersecurity

Data-driven predictive models

Data-driven predictive models exploit automated learning algorithms in an attempt to adapt their prediction based on data-driven learning approaches, constantly updating detection and prevention procedures, and based on dynamically identified behavior patterns.

The algorithms that are used in data-driven predictive models are derived from distinct fields of quantitative analysis, starting from statistics, ending in data mining and ML, and having an objective of learning about hidden or latent patterns within the data.

The privileged role of ML algorithms in the implementation of data-driven predictive models is immediately evident; ML makes it possible to identify predictive models based on the training that's ...