Malware Data Science: Attack Detection and Attribution (True MOBI)-P2P
Malware Data Science explains how to identify, analyze, and classify large-scale malware using machine learning and data visualization.
Security has become a “big data” problem. The growth rate of malware has accelerated to tens of millions of new files per year while our networks generate an ever-larger flood of security-relevant data each day. In order to defend against these advanced attacks, you’ll need to know how to think like a data scientist.
In Malware Data Science, security data scientist Joshua Saxe introduces machine learning, statistics, social network analysis, and data visualization, and shows you how to apply these methods to malware detection and analysis.

Malware Data Science: Attack Detection and Attribution (True MOBI)-P2P
English | 2019 | ISBN-13: 978-1593278595 | 272 Pages | True MOBI | 47.69 MB
Download: NITROFLARE

Comments (3)
https://katfile.com/lgjg0znbhzm1/978-1593278595.mobi.html
Malware Data Science: Attack Detection and Attribution (True MOBI)-P2P
https://dropapk.to/c5ruhcg50fk1
https://ddownload.com/4anijvx4zw0s
https://dailyuploads.net/pdws07vnw22k
https://giga-down.com/3jsuqgookv2w
Malware Data Science: Attack Detection and Attribution (True MOBI)-P2P
https://katfile.com/7vae0sabicaq/978-1593278595.mobi.html