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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| Formato: | Libro electrónico |
| Idioma: | Inglés |
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Indianapolis, Indiana :
John Wiley & Sons
2014.
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| Edición: | 1st edition |
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| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009627943306719 |
Tabla de Contenidos:
- Cover; Title Page; Copyright; Contents; Introduction; Overview of the Book and Technologies; How This Book Is Organized; Who Should Read This Book; Tools You Will Need; What's on the Website; The Journey Begins!; Chapter 1 The Journey to Data-Driven Security; A Brief History of Learning from Data; Nineteenth Century Data Analysis; Twentieth Century Data Analysis; Twenty-First Century Data Analysis; Gathering Data Analysis Skills; Domain Expertise; Programming Skills; Data Management; Statistics; Visualization (a.k.a. Communication); Combining the Skills; Centering on a Question
- Creating a Good Research Question Exploratory Data Analysis; 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?; Why Python?; Why R?; Why Both?; Jump starting Your Python Analytics with Canopy; Understanding the Python Data Analysis and Visualization Ecosystem; Setting Up Your R Environment; 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; Summary; Recommended Reading; Chapter 4 Performing Exploratory Security Data Analysis; Dissecting the IP Address; Representing IP Addresses; Segmenting and Grouping IP Addresses; Locating IP Addresses; Augmenting IP Address Data; Association/Correlation, Causation, and Security Operations Center Analysts Gone Rogue; Mapping Outside the Continents; Visualizing the ZeuS Botnet; Visualizing Your Firewall Data; Summary; Recommended Reading; Chapter 5 From Maps to Regression; Simplifying Maps; How Many Zero Access Infections per Country?
- Changing the Scope of Your Data The Potwin Effect; Is This Weird?; Counting in Counties; Moving Down to Counties; Introducing Linear Regression; Understanding Common Pitfalls in Regression Analysis; Regression on Zero Access Infections; Summary; Recommended Reading; Chapter 6 Visualizing Security Data; Why Visualize?; Unraveling Visual Perception; Understanding the Components of Visual Communications; Avoiding the Third Dimension; Using Color; Putting It All Together; Communicating Distributions; Visualizing Time Series; Experiment on Your Own; Turning Your Data into a Movie Star; Summary
- Recommended Reading Chapter 7 Learning from Security Breaches; Setting Up the Research; Considerations in a Data Collection Framework; Aiming for Objective Answers; Limiting Possible Answers; Allowing "Other," and "Unknown" Options; Avoiding Conflation and Merging the Minutiae; An Introduction to VERIS; Incident Tracking; Threat Actor; Threat Actions; Information Assets; Attributes; Discovery/Response; Impact; Victim; Indicators; Extending VERIS with Plus; Seeing VERIS in Action; Working with VCDB Data; Getting the Most Out of VERIS Data; Summary; Recommended Reading
- Chapter 8 Breaking Up with Your Relational Database
