Malware Data Science

Attack, Detection, and Attribution

Joshua Saxe, Hillary Sanders (Autoren)

Buch | Softcover

272 Seiten

2018
No Starch Press,US (Verlag)
978-1-59327-859-5 (ISBN)

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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.

Joshua Saxe is Chief Data Scientist at major security vendor, Sophos, where he leads a security data science research team. He's also a principal inventor of Sophos' neural network-based malware detector, which defends tens of millions of Sophos customers from malware infections. Before joining Sophos, Joshua spent 5 years leading DARPA funded security data research projects for the US government. Hillary Sanders leads the infrastructure data science team at Sophos, which develops the frameworks used to build Sophos' deep learning models. Before joining Sophos, Hillary created a recipe web app and spent three years as a data scientist at Premise Data Corporation.

Erscheinungsdatum	28.09.2018
Zusatzinfo	1 Illustrations
Verlagsort	San Francisco
Sprache	englisch
Maße	178 x 235 mm
Gewicht	622 g
Themenwelt	Informatik ► Netzwerke ► Sicherheit / Firewall
ISBN-10	1-59327-859-4 / 1593278594
ISBN-13	978-1-59327-859-5 / 9781593278595
Zustand	Neuware