Read e-book online Data-Driven Security: Analysis, Visualization and Dashboards PDF
By Jay Jacobs, Bob Rudis
Uncover hidden styles of knowledge and reply with countermeasures
Security pros desire all of the instruments at their disposal to extend their visibility on the way to hinder safety breaches and assaults. This cautious consultant explores of the main strong ? info research and visualization. You'll quickly know the way to harness and wield facts, from assortment and garage to administration and research in addition to visualization and presentation. utilizing a hands-on process with real-world examples, this e-book indicates you the way to assemble suggestions, degree the effectiveness of your safety tools, and make larger decisions.
Everything during this publication could have functional software for info safety professionals.
is helping IT and defense pros comprehend and use info, to allow them to thwart assaults and comprehend and visualize vulnerabilities of their networks
comprises greater than a dozen real-world examples and hands-on routines that exhibit find out how to examine defense info and intelligence and translate that info into visualizations that make undeniable find out how to hinder attacks
Covers issues corresponding to the best way to collect and get ready protection information, use easy statistical how you can observe malware, are expecting rogue habit, correlate safeguard occasions, and more
Written through a workforce of famous specialists within the box of protection and knowledge analysis
Lock down your networks, hinder hacks, and thwart malware through bettering visibility into the surroundings, throughout the ability of knowledge and Security utilizing info research, Visualization, and Dashboards.
Read or Download Data-Driven Security: Analysis, Visualization and Dashboards PDF
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Additional info for Data-Driven Security: Analysis, Visualization and Dashboards
Therefore, every good data analysis project begins by setting a goal and creating one or more research questions. ” That reaction is probably caused by the lack of a well-prepared research question in the analysis. Remember, the purpose of data analysis is to learn from the environment; learning can be done with or without data (with varying degrees of success). Creating and following a good research question is a component of good learning, not just of good data analysis. Without a well-formed question guiding the analysis, you may waste 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.
Having built up the application of statistics on a pedestal, we should point out that you can learn a lot from data without advanced statistical techniques. Recall the “descriptive visualization” mentioned previously. Take some time to look around at many of visualizations out there; they are generally not built from statistical models, but describe some set of data and show the relationships therein. Snow’s map of the areas around the water pump on Broad Street in Figure 1-1 did not involve logistic regression or machine learning; this map was just a visual description of the relationship between address and deaths.
It’s the process of walking around barefoot in the data, perhaps even rolling around a bit in it. You do this to learn about the variables in the data, their signiﬁcance, and their relationships to other variables. Tukey developed a whole range of techniques to increase your visibility into and understanding of the data, including the elegantly simple stem and leaf plot, the five-number summary, and the helpful box plot diagram. Each of these techniques is explained or used later in this book. Once you get comfortable with the data, you’ll naturally start to ask some question of it.
Data-Driven Security: Analysis, Visualization and Dashboards by Jay Jacobs, Bob Rudis