
Learn security visualization by exploring data sources, use cases, and display types, applying practical methods and standards to create clear security data visuals.
Preview the course contents, explore the examples and MPD sources, and review the quiz questions to gain confidence in the security data visualization course.
Examine how standards give rise to data formats and influence security data visualization. Identify how citations and online sources shape the use of these formats.
Master quick file export exercises using Wireshark to visualize security data, exploring practical techniques for exporting data for analysis and visualization.
Practice quick log parser exercises using API queries and markers, with sample log data and instructions to generate output files, aligning with the prior lecture.
Explore the first part of the 25-step security visualization design process. Focus on decision making, planning, and data source choices for targeted threats.
Explore visual representations of data for security visualization, focusing on display type selection, simple design, and storytelling through appropriate charts such as line, bar, and pie charts.
Learn to design radial and circular displays that convey relationships, time, and system metrics through concentric circles, color, and patterns, including error distributions and server connectivity.
Visualize security data with node link diagrams by mapping relationships, interactions, and routes among autonomous systems using color-coded nodes and directional links.
Explore how miscellaneous displays in security data visualization use depth illusions from two slightly different images, emphasize the region the user is at, and apply neural networks for classification.
Learn to prepare external data with Python by reading, cleaning, and transforming various file types, including Excel, CSV, and JSON, and creating data frames for visualization and basic analysis.
Explore quick exercises for visualizing data with Python Matplotlib, learning to create figures, set axes, annotate points, and build bar, pie, and scatter plots.
Explore quick exercises using Python and Matplotlib to monitor IIS server traffic, reading external data files with pandas, and visualizing bytes sent and received, client IPs, and usernames.
Learn Security Visualization by Examples.
The objectives of this course include :
Going over security visualization data sources and ways of collecting data for visualization purposes;
Depicting all the popular security visualization use-cases (not just focusing network data visualization);
Teaching more than 50 display properties/types which are best associated with some specific security data or security use-cases.
At the end of this course, you will learn about :
Security Visualization Basics
Security Data Sources
Security Use-Cases
Basic Security Analyses Types
Various Display Types and Properties Which are Useful for the Visualization of Security Data
Most Useful Interaction Techniques
Technologies in a Nutshell- Quick Starter Guide and Exercises for Most Relevant Technologies
Related Academic Studies
Security Data Formats Standards Information