PDF Download Malware Data Science: Attack Detection and Attribution, by Joshua Saxe
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Malware Data Science: Attack Detection and Attribution, by Joshua Saxe
PDF Download Malware Data Science: Attack Detection and Attribution, by Joshua Saxe
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Review
"For those looking to become a security data scientist, or just want to get a comprehensive understanding of how to use data science to deal with malicious software, Malware Data Science is a superb reference." —Ben Rothke, RSA Conference
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About the Author
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.
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Product details
Paperback: 272 pages
Publisher: No Starch Press (September 25, 2018)
Language: English
ISBN-10: 9781593278595
ISBN-13: 978-1593278595
ASIN: 1593278594
Product Dimensions:
7 x 0.8 x 9.2 inches
Shipping Weight: 1.4 pounds (View shipping rates and policies)
Average Customer Review:
4.7 out of 5 stars
4 customer reviews
Amazon Best Sellers Rank:
#97,751 in Books (See Top 100 in Books)
I loved this book, it gives you a quick intro to disassemble and "reverse engineering", and it states that if you want to go deeper you can read Practical Malware analysis, which I think could be the next level of this book, from there it's just a roller coaster of binary data analysis, data visualization and coding. Joshua and Hillary made a good job at keeping the code readable, while teaching some key concepts on ML and deep learning, data visualization and analysis. In the end, the book not only feeds you with plenty of information, but also is able to give you new ideas.
Wow, this is one amazing introduction. I’m usually reading other bug hunting books, then I came upon this book. I kind of shined away from machine learning, however this book provided me with surprises, pleasent ones. A very 8nteresting book.
The intersection of data science and infosec is smaller than should be. The authors have done a great job explaining complex topics clearly, and with good code.
The proverb “Give a man a fish and you feed him for a day; teach a man to fish and you feed him for a lifetime,†is known by almost everyone. In Malware Data Science: Attack Detection and Attribution, authors Joshua Saxe and Hillary Sanders artfully show the reader how not only to avoid being a victim of malicious code, but how to actively defend against it, and even build your own systems to do that.Malware is such a huge issue, that many anti-virus vendors update their signatures hourly to deal with the never-ending set of threats. The authors work at Sophos (Chief Data Scientist and Infrastructure Data Science Team Lead, respectively) and have written a highly technical and effective guide that readers can use to implement their own defensive systems.At the start, the authors define data science as, “A growing set of algorithmic tools that allow users to understand and make predictions about data using statistics, mathematics, and artful statistical data visualizations.†The book focuses on data science as it applies to malware, which they define as, “executable programs written with malicious intent.â€The book is meant as an introduction to the use of data science to malware analysis and detection. The authors take a broad approach to the topic and discuss static malware analysis, x86 disassembly, dynamic analysis and identifying attack campaigns using malware networks. Later chapters detail how the reader can build machine learning detectors, neural network malware detector, and more.The book is insightful for all information security professionals in general, but more specifically those who code and can read code, specifically in Python. The authors provide many code and data samples and have included all of them on the book’s web site. There the reader can also find instructions for downloading and running a VirtualBox Ubuntu virtual machine which contains the book's code, data, and all of the requisite dependencies.The book closes with a chapter on becoming a data scientist, where the authors discuss the paths to becoming a security data scientist and a day in the life of a security data scientist. More importantly, they detail the traits of an effective security data scientist. For those looking to become a security data scientist, or just want to get a comprehensive understanding of how to use data science to deal with malicious software, Malware Data Science: Attack Detection and Attribution is a superb reference to help you get there.
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