Developing predictive defenses
Being able to predict the future is something that everyone who is involved with security would like to have. The use of ML to help predict things such as network attacks is an ongoing venture, but there aren’t any commercial examples of such technology to date, and usable examples are also hard to find. However, it’s possible to postulate what a commercial offering might look like and start doing some experimenting of your own, as described in the sections that follow.
Defining what is available today
What you see most often today are explorations into predictive software based on new Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), and Multilayer Perceptron (MLP) models, which are described in articles such as CyberSecurity Attack Prediction: A Deep Learning Approach at https://dl.acm.org/doi/fullHtml/10.1145/3433174.3433614 and A deep learning framework for predicting cyber attacks rates at https://link.springer.com...
