Data-Driven Security: Analysis, Visualization and Dashboards

by Jay Jacobs, Bob Rudis

Everything in the book will have practical application for information security professionals. The entire purpose of data analysis and visualization is to gather feedback from the environment to make better and more informed technology decisions. Within information security that means identifying ways to prevent or detect breaches and then measuring the effectiveness in doing so, which is all wrapped up under "risk management." All of the examples will be directed at answering real-world questions. One of the key points is not just to analyze what is in front of us, but collect and analyze the data we need to answer the questions that will lead to better decisions and prevention of hacks and vulnerabilities.

The book will present the core elements of analyzing I.T. system data and information security feedback by using 30 use cases and domain-specific data sets with a focus on practical "how-to." This hands-on approach will be covered in context and will not be limited to just the analysis, but all the supporting skills needed to learn from our data. Data analysis from start to finish: from the data collection and preparation through the data storage and management fundamentals then into the analysis and finally data visualization and communication techniques all in the context of security.Use cases will include: Discovering anomalous firewall trafficHow to acquire and prepare security dataCreating a repeatable data analysis toolkit and workflowWhitehat stats reportSecurity event correlationVulnerability countsUsing inferential stats to detect malware outbreaksVisualizing system logsMapping BotnetsUsing NLP and Data Loss PreventionPredicting rogue behaviorHow to perform predictive analytics

Genres: Reference, Technology, Technical, Nonfiction

352 pages, Kindle Edition

First published January 1, 2014

Reviews

[Peter Zvirinsky · Rating 1 out of 5]

I have seen this book referenced a couple of times as "the" book about how data science/ML can be applied in the security field. However, after reading it, I have to say I don't understand who is this book for. Because if you are a data scientist, this book will not be enough to get you going in the security field and vice versa, if you are a security person, you will not learn how to do data science from this book.

I appreciate the introduction; it is very well written, and succinctly states the arguments for why data-driven decision making is important for the security field. It even provides a nice quick historical context for the ML & stats fields for the layman. However, starting chapter number two, it is only worth skimming through, there is just not enough information to make it worthwhile. The most valuable are perhaps the materials referenced at the end of every chapter.

[Billford · Rating 4 out of 5]

Good overview at building data into infosec decisions

I liked the build up structure of the book and the way it showed how you would use some of the examples in real life. I would've liked a little more explanation behind why you would use one statistical model over another but overall very nicely done.

[Andre · Rating 4 out of 5]

The future of Infoseek lies in this direction. A must read if you don't want to miss the boat. I know where to take my team in 2016-17.

[Delhi Irc]

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