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Data-Driven Security: Analysis, Visualization and Dashboards 1st Edition

4.5 out of 5 stars 17 customer reviews
ISBN-13: 978-1118793725
ISBN-10: 1118793722
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Editorial Reviews

From the Back Cover

A practical guide to securing your data and IT infrastructure

From safeguarding corporate data to keeping e-commerce transactions secure, today’s IT professionals are tasked with enormous and complex data security responsibilities. In Data-Driven Security, Jay Jacobs and Bob Rudis draw together three of the most important topics in IT—security, data analysis, and visualization—to present a real-world security strategy to defend your networks. Turning their backs on insufficient security based on hunches and best practices, the authors help you access the world of security data analysis and visualization, where real data drives security decisions, and they teach you to apply the principles of that security with real-world cases.

  • Develop an understanding of how to acquire, prepare, and visualize security data
  • Learn how to use the analytical and visualization tools in R and Python
  • Dissect IP addresses to find malicious activity
  • Map security data and learn statistical techniques to look for significant connections
  • Understand how visual communication works and how it can help you see and present your data clearly
  • Develop effective, informative security dashboards
  • Design analytical models to help you detect malicious behavior
  • Gain practical “how-to” knowledge from specific, real-world use cases detailing an array of data and network security scenarios

Visit the companion website at www.wiley.com/go/datadrivensecurity for additional information and resources

About the Author

Jay Jacobs is the coauthor of Verizon Data Breach Investigation Reports and the cofounder of the Society of Information Risk Analysts, where he currently sits on the board of directors.

Bob Rudis is the Director of Enterprise Information Security & IT Risk Management at Liberty Mutual Insurance and was named one of the Top 25 Influencers in Information Security by Tripwire.

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Product Details

  • Paperback: 352 pages
  • Publisher: Wiley; 1 edition (February 24, 2014)
  • Language: English
  • ISBN-10: 1118793722
  • ISBN-13: 978-1118793725
  • Product Dimensions: 7.4 x 0.7 x 9.1 inches
  • Shipping Weight: 1.8 pounds (View shipping rates and policies)
  • Average Customer Review: 4.5 out of 5 stars  See all reviews (17 customer reviews)
  • Amazon Best Sellers Rank: #187,649 in Books (See Top 100 in Books)

Customer Reviews

Top Customer Reviews

Format: Paperback
There is a not so fine line between data dashboards and other information displays that provide pretty but otherwise useless and unactionable information; and those that provide effective answers to key questions. Data-Driven Security: Analysis, Visualization and Dashboards is all about the later.

In this extremely valuable book, authors and noted experts Jay Jacobs and Bob Rudis bring their decades of experience to the reader and show you how to find security patterns in your data logs and extract enough information from it to create effective information security countermeasures. By using data correctly and truly understanding what that data means, the authors show how you can achieve much greater levels of security.

The book is meant for a serious reader who is willing to put in the time and effort to learn the programming necessary (mainly in Python and R) to truly understand what information exists deep in the recesses of their logs. As to R, it is a GNU project and a free software programming language and software environment for statistical computing and graphics. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. For analysis the level of which Jacobs and Rudis prescribe, R is a godsend.
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Format: Paperback Verified Purchase
In the past 6 months I have read everything I could by Edward Tufte, Stephen Few, and Nathan Yau. I have read the collection of essays contained in "Beautiful Visualization", the heavy tome "Information Visualization" by Colin Ware, "Naked Statistics" by Charles Wheelan and many many more white papers. I am hardly an expert in the field of "Data Security Visualization" but I am at least very well read in the subject.

...saying that had this book been out when I started, I could have just read it instead. The authors do a fantastic job at parsing the most important messages and examples from each book and seamlessly integrate it into an engaging read. There is a little bit of a (dare I say) sales pitch about specific toolsets the authors are vested in, but that makes sense. That is why they are subject matter experts in the field. I cannot recommend this book enough to anyone who wants to start making sense of statistics and visualizations in the cyber security field. It is even a good book for people who are experts as it provides the "one stop shop" for many of the facts and lessons contained in the aforementioned bibliography.
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Format: Paperback
The book covers the concepts, tools and techniques that can be used to analyze different types of information security data sets and explains many of the common pitfalls in both approach and interpretation of the results of this analysis. It's effectively a perfect introduction to data science/analysis for information security!

The book starts off by introducing the reader to what data analysis is, covering historical concepts and how to create a good question to answer with analysis, rather than simply analyzing data for the sake of it.

It then moves on to provide an introduction to the R programming language, a free statistical programming language, and also how they us Python in conjunction with R to analyze data.

The book is very practically oriented, encouraging the reader to start playing around with both Python and R by providing full coded examples of all the analysis performed in each chapter. To make life easier, all the code examples can be downloaded from the books website and any data sets used for analysis are either publicly available already or can be downloaded with the source code.

Once you get your head around the basics of using the tools for analysis, the book then walks through examples of the different types of analysis that information security data sets may require, covering things like exploring data sets of malware infections, performing regression analysis on malware data and applying machine learning to breach data. Throughout the examples, the book puts a strong emphasis on visualization of data including both the common mistakes in presenting data analysis and also looks both at static and interactive visualization.
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Although I'm not the target market for this book (I'm not an IT professional), I wanted to learn more about visualizations of data and Chapter 6 fit the bill. I think this book would be very useful to IT professionals who want to learn more about security techniques and creating visualizations to analyze and explain what's happening in their systems.
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