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Data-Driven Security : Analysis, Visualization and Dashboards.

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'...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Jacobs, Jay (Data analyst)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Wiley, 2014.
©2014
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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520 |a 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 ma. 
504 |a Includes bibliographical references. 
505 0 |a Introduction; Chapter 1: The Journey to Data-Driven Security; A Brief History of Learning from Data; Gathering Data Analysis Skills; Centering on a Question; Summary; Recommended Reading; Chapter 2: Building Your Analytics Toolbox: A Primer on Using R and Python for Security Analysis; Why Python? Why R? And Why Both?; Jumpstarting Your Python Analytics with Canopy; Introducing Data Frames; Organizing Analyses; Summary; Recommended Reading; Chapter 3: Learning the Hello World of Security Data Analysis; Solving a Problem; Getting Data; Reading In Data; Exploring Data; Homing In on a Question. 
505 8 |a Considerations in a Data Collection FrameworkAn Introduction to VERIS; Seeing VERIS in Action; Working with VCDB Data; Summary; Recommended Reading; Chapter 8: Breaking Up With Your Relational Database; Realizing the Container Has Constraints; Exploring Alternative Data Stores; Summary; Recommended Reading; Chapter 9: Demystifying Machine Learning; Detecting Malware; Benefiting from Machine Learning; Specific Learning Methods; Hands On: Clustering Breach Data; Summary; Recommended Reading; Chapter 10: Designing Effective Security Dashboards; What Is a Dashboard, Anyway? 
505 8 |a Chapter 11Chapter 12; R Packages Used. 
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