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Data-Driven Security: Analysis, Visualization and Dashboards

Data-Driven Security: Analysis, Visualization and Dashboards [Kindle Edition]

Jay Jacobs , Bob Rudis

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Product Description

Product Description

Uncover hidden patterns of data and respond with countermeasures

Security professionals need all the tools at their disposal to increase their visibility in order to prevent security breaches and attacks. This careful guide explores two of the most powerful ? data analysis and visualization. You'll soon understand how to harness and wield data, from collection and storage to management and analysis as well as visualization and presentation. Using a hands-on approach with real-world examples, this book shows you how to gather feedback, measure the effectiveness of your security methods, and make better decisions.

Everything in this book will have practical application for information security professionals.

  • Helps IT and security professionals understand and use data, so they can thwart attacks and understand and visualize vulnerabilities in their networks
  • Includes more than a dozen real-world examples and hands-on exercises that demonstrate how to analyze security data and intelligence and translate that information into visualizations that make plain how to prevent attacks
  • Covers topics such as how to acquire and prepare security data, use simple statistical methods to detect malware, predict rogue behavior, correlate security events, and more
  • Written by a team of well-known experts in the field of security and data analysis

Lock down your networks, prevent hacks, and thwart malware by improving visibility into the environment, all through the power of data and Security Using Data Analysis, Visualization, and Dashboards.

From the Back Cover

A practical guide to securing your data and IT infrastructure From safeguarding corporate data to keeping e–commerce transactions secure, todays 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 ITsecurity, data analysis, and visualizationto 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 for additional information and resources

Product details

  • Format: Kindle Edition
  • File Size: 40762 KB
  • Print Length: 352 pages
  • Publisher: Wiley; 1 edition (24 Jan 2014)
  • Sold by: Amazon Media EU S.à r.l.
  • Language: English
  • ASIN: B00I1Y7THY
  • Text-to-Speech: Enabled
  • X-Ray:
  • Amazon Bestsellers Rank: #37,754 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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Most Helpful Customer Reviews on (beta) 4.9 out of 5 stars  9 reviews
4 of 4 people found the following review helpful
5.0 out of 5 stars Excellent Primer on All Things Info Sec Data Analysis 17 Mar 2014
By Mairtin O. Sullivan - Published on
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.

Overall I thoroughly enjoyed reading this book and while I haven't had the time to start looking at applying the ideas in the book to my own data sets, it's opened up a whole world of analysis tools and techniques and has effectively shortcutted my learning in the area dramatically.

The biggest benefit I see from this book is the highly practical oriented approach, which allows anyone with an interest in information security data analysis to quickly get up to speed in the basics, allowing for them to at least have the tools and knowledge to start trying to ask interesting questions and get results, without having to re-invent the wheel.

If you've ever been sitting in front of a huge set of firewall or webserver logs during an incident trying to figure things out by greping, cuting and counting results you're going to get a lot from this book!
2 of 2 people found the following review helpful
5.0 out of 5 stars Superb book for effective use of data to drive information security 7 July 2014
By Ben Rothke - Published on
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.

The following are the 12 densely packed chapters in the book:

1 : The Journey to Data-Driven Security
2 : Building Your Analytics Toolbox: A Primer on Using R and Python for Security Analysis
3 : Learning the "Hello World" of Security Data Analysis
4 : Performing Exploratory Security Data Analysis
5 : From Maps to Regression
6 : Visualizing Security Data
7 : Learning from Security Breaches
8 : Breaking Up with Your Relational Database
9 : Demystifying Machine Learning
10 : Designing Effective Security Dashboards
11 : Building Interactive Security Visualizations
12 : Moving Toward Data-Driven Security

After completing the book, the reader will have the ability to know which questions to ask to gain security insights, and use that data to ensure the overall security of their data and networks. Getting to that level is not a trivial at all a trivial task; even if there are vendors who can promise to do that.

For many people performing data analysis, the dependable Excel spreadsheet is their basic choice for data manipulation. The book calls the spreadsheet a gateway tool between a text editor and programming. The book notes that spreadsheets work as long as the data is not too large or complex. The book quotes a 2013 report to shareholders from J.P. Morgan in which parts of their 2012 $6 billion in losses was due in part to problems with their Excel spreadsheets.

The authors suggest using Excel as a temporary solution for quick one-shot tasks. For those that have repeating analytical tasks or models that are used repeatedly, it's best to move to some type of structured programming language, specifically those that the book suggest and for provides significant amounts of code examples.

The goal of all data extraction is to use data analysis to answer real questions. A large part of the book focuses on how to ask the right question. In chapter 1, the authors write that every good data analysis project begins with setting a goal and creating one or more research questions. Without a well-formed question guiding the analysis, you may wasting time and energy seeking convenient answers in the data, or worse, you may end up answering a question that nobody was asking in the first place.

The value of the book is that it shows the reader how to focus on context and purpose of the data analysis by setting the research question appropriately; rather than simply parsing large amounts of data. It's ultimately irrelevant if you can use Hadoop to process petabytes of data if you don't know what you are looking for.

Visualization is a large part of what this book is about, and in chapter 6 - Visualizing Security Data, the book notes that the most efficient path to human understanding is via the visual sense. It goes on to details the many advantages data visualization has, and the key to making it work.

As important as visualization is, describing the data is equally important. In chapter 7, the book introduces the VERIS (Vocabulary for Event Recording and Incident Sharing) framework. VERIS is a set of metrics designed to provide a common language for describing security incidents in a structured and repeatable manner. VERIS helps organizations collect useful incident-related information and to share that information, anonymously and responsibly with others.

The book shows how you can use dashboards for effective data visualization. But the authors warn that a dashboard is not an art show. They caution that given the graphical nature of dashboards, it's easy to fall into the trap of making them look like pieces of modern or fringe art; when they are far more akin to architectural and industrial diagrams that require more controlled, deliberate and constrained design.

The book uses the definition of dashboard according to Stephen Few, in that it's a "visual display of the most important information needed to achieve one or more objectives that has been consolidated in a single computer screen so it can be monitored at a glance". The book enables the reader to create dashboards like that.

Data-Driven Security: Analysis, Visualization and Dashboards is a superb book written by two experts who provide significant amounts of valuable information in every chapter. For those that are willing to put the time and effort into the serious amount of work that the book requires, they will find it a vital resource that will certainly help them achieve much higher levels of security.
2 of 2 people found the following review helpful
5.0 out of 5 stars Combines the best of all worlds 27 Mar 2014
By R. Kovar - Published on
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.
1 of 1 people found the following review helpful
5.0 out of 5 stars Clearly written, beautifully designed 14 April 2014
By J. Veltsos - Published on
Format:Paperback|Verified Purchase
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.
1 of 1 people found the following review helpful
5.0 out of 5 stars Excellent book for security professionals look to learn data security and the tools - python, R project, .... 16 Feb 2014
By Valdez Ladd - Published on
Format:Kindle Edition|Verified Purchase
Excellent book for security professionals look to learn data security and many of the tools used today.

I am using it along with other data visualization book to learn this area of expertise.

IT Security Analyst, Intelligence Analyst, and others will be expected to use and produce actionable risk analysis, audit analysis and business intelligence integration between security and business process owners.
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