Description
| Product ID: | 9781593278595 |
| Product Form: | Paperback / softback |
| Country of Manufacture: | US |
| Title: | Malware Data Science |
| Subtitle: | Attack, Detection, and Attribution |
| Authors: | Author: Hillary Sanders, Joshua Saxe |
| Page Count: | 272 |
| Subjects: | Computer programming / software engineering, Computer programming / software development |
| Description: | Select Guide Rating Identify, analyse, and classify large-scale malware using machine learning and data visualisation. 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 visualisation, and shows you how to apply these methods to malware detection and analysis. |
| Imprint Name: | No Starch Press,US |
| Publisher Name: | No Starch Press,US |
| Country of Publication: | GB |
| Publishing Date: | 2018-09-25 |
