Data-Driven Security: Analysis, Visualization and Dashboards by Jay Jacobs, Bob Rudis

By Jay Jacobs, Bob Rudis

Uncover hidden styles of knowledge and reply with countermeasures

Security execs want the entire instruments at their disposal to extend their visibility so one can hinder defense breaches and assaults. This cautious consultant explores of the main strong ? information research and visualization. You'll quickly know how to harness and wield info, from assortment and garage to administration and research in addition to visualization and presentation. utilizing a hands-on process with real-world examples, this publication indicates you ways to collect suggestions, degree the effectiveness of your safety equipment, and make larger decisions.

Everything during this publication can have functional software for info defense professionals.

is helping IT and protection execs comprehend and use facts, to allow them to thwart assaults and comprehend and visualize vulnerabilities of their networks
contains greater than a dozen real-world examples and hands-on workouts that display the right way to research defense information and intelligence and translate that info into visualizations that make undeniable how you can hinder attacks
Covers subject matters reminiscent of tips on how to collect and get ready defense facts, use uncomplicated statistical how you can observe malware, expect rogue habit, correlate protection occasions, and more
Written by means of a crew of famous specialists within the box of safeguard and knowledge analysis

Lock down your networks, hinder hacks, and thwart malware by means of enhancing visibility into the surroundings, throughout the ability of information and Security utilizing facts research, Visualization, and Dashboards.

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For example, statisticians developed the R language specifically for the purpose of performing data analysis. Python—with the addition of packages like NumPy, SciPy, and pandas—offers a rich and comparable data analysis environment. But, preparing and analyzing the data is not enough. You also need to communicate your results, and one of the most effective methods for that is data visualization (covered in several chapters of this book). Again, Excel can produce graphics. With judicial modification of the default settings, you can get good visualization with Excel.

7, and a good number of packages have updated to be compatible with the newer version. 7. 7 make it a good choice to begin exploring Python for data analysis. html). com/ide/download/). indd 11:15:24:AM 12/31/2013 Page 29 29 30 BUILDING YOUR ANALYTICS TOOLBOX Both links provide full installation details for Linux, Windows, and Mac OS X systems, so we won’t delve into the minutiae in this section. You do, however, need to make a choice when you install RStudio, as it comes in two flavors: Desktop and Server.

If they wanted to know which presidential candidate would get the most votes among Americans with a phone, club membership, or magazine subscription, the data told an accurate story. However, they weren’t looking for that story. They wanted to know about all registered voters in the United States, but through their selection of sources they introduced bias into their sample and drew meaning from the data that simply did not exist. The fact that they had an unprecedented 2 million responses did not help improve the accuracy of their poll.

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