Security Data Visualization

Define data visualization and security visualization to show how visual representations reveal patterns in security data, supporting monitoring, analysis, and storytelling across security scenarios.

Explore classifications of security visualization designs, based on technology and data, to guide focused design decisions for specific data intents. Review the bibliography for further studies.

Preview the course contents, explore the examples and MPD sources, and review the quiz questions to gain confidence in the security data visualization course.

Explore design problems in security data visualization, including scaling for data size and dimensions, data source integration, real-time versus historic analysis, and reporting.

Explore scientific reading on design issues and design problems, review ten more articles, and verify suitable learning material using the learning code in section 1.

Introduce security data and its data types, and examine common problems such as missing data and issues from multiple sources to guide effective visualization and analysis.

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.

Identify security data sources, from network traffic in pcap format to intrusion detection system logs, and learn to collect and analyze them with tcpdump and Wireshark.

Learn how tcpdump and windump capture and filter network traffic on Linux, Unix, and Windows, save to a universal capture format or read from it, with installation and usage tips.

Perform quick tcpdump windump exercises by selecting an interface and starting packet capture. Save to a file with -w, apply filters, disable name resolution, and limit packets with -c.

Learn about Wireshark, the free open-source packet analyzer for network troubleshooting, education, and protocol development. Use the interface to filter data by protocol, IP, or port and export for visualization.

Master quick file export exercises using Wireshark to visualize security data, exploring practical techniques for exporting data for analysis and visualization.

Install Microsoft Log Parser on Windows and learn to query log data, with steps and tips for writing results to files in multiple formats.

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.

Learn the second part of the 25-step security visualization design process, covering planning, data preparation, tool integrations, and using aggregations, timing analyses, and validations to reveal vulnerabilities.

Define use cases in software and security visualization by identifying actors and system interactions to achieve goals, with examples like network traffic analysis and visualization design.

Explore enterprise security data visualization use cases, including sunburst visualizations of firewall rules, ATP traffic analysis, and trust-based network relationships for real-time threat understanding.

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.

Prepare data for visualization by selecting compatible formats, labeling clearly, and organizing datasets for visualization technologies used by technology companies.

Design simple charts, tables, and formatted text to clearly present security data, emphasizing comprehensible presentation, time-based comparisons, and addressing the needs of end users and upper level managers.

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.

Explore how parallel axis view enables multi-axis data visualization with colors, labels, and adjustable timeframes. Compare circular and hierarchical designs and learn open-source options and custom implementations.

Visualize security data with node link diagrams by mapping relationships, interactions, and routes among autonomous systems using color-coded nodes and directional links.

Explore the use of dashboards, hierarchical views, and maps to visualize security data and present multiple perspectives of the same data to support teamwork.

Explore matrices, x-y plots, and scatter plots to visualize security data, using colors, shapes, and connections to reveal state information.

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 visualize data with Python using essential libraries such as NumPy, Pandas, Matplotlib, and Seaborn, and follow an installation guide with Anaconda and Jupyter notebooks.

Explore Python data structures for data visualization, including dictionaries, series, and data frames, and learn to create, access, modify, and select data using NumPy and Pandas in Jupyter notebooks.

Learn to prepare data with Python by performing core data operations, merging, reshaping, generating random data, handling missing values, and filtering by conditions, to support effective visualization.

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.

Create an attack graph with the Python Graphviz library, detailing nodes, edges, labels, and dot files for visualization, then refine visuals using color, shape, and thickness.

Leverage interactivity in security data visualization to improve effective communication, enabling exploration through input controls, geo maps, and ip/port data for deeper analysis.

Thank you and congratulations on completing this course. Celebrate your confidence to work with security data and create useful digital visualizations for your specific purpose.

Compile references and resources for security data visualization, including data point visualizations, crisis management techniques and protocols, and information security literature, with JavaScript data presentation tools.