Skip to Content
Machine Learning for Cybersecurity Cookbook
book

Machine Learning for Cybersecurity Cookbook

by Emmanuel Tsukerman
November 2019
Intermediate to advanced content levelIntermediate to advanced
346 pages
9h 36m
English
Packt Publishing
Content preview from Machine Learning for Cybersecurity Cookbook

How it works...

We start by importing our dataset of PE header information from a collection of samples (step 1). This dataset consists of two classes of PE files: malware and benign. We then use plotly to create a nice-looking interactive 3D graph (step 1). We proceed to prepare our dataset for machine learning. Specifically, in step 2, we set X as the features and y as the classes of the dataset. Based on the fact that there are two classes, we aim to cluster the data into two groups that will match the sample classification. We utilize the K-means algorithm (step 3), about which you can find more information at: https://en.wikipedia.org/wiki/K-means_clustering. With a thoroughly trained clustering algorithm, we are ready to predict on ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Hands-On Machine Learning for Cybersecurity

Hands-On Machine Learning for Cybersecurity

Soma Halder, Sinan Ozdemir
Machine Learning on Kubernetes

Machine Learning on Kubernetes

Faisal Masood, Ross Brigoli

Publisher Resources

ISBN: 9781789614671Supplemental Content