February 2014
Beginner
348 pages
9h 13m
English
Content preview from Network Security Through Data AnalysisBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Chapter 13. Graph Analysis
A graph is a mathematical construct composed of one or more nodes (or vertices) connected together by one or more links (or edges). Graphs are an effective way to describe communication without getting lost in the weeds. They can be used to model connectivity and provide a comprehensive view of that connectivity while abstracting away details such as packet sizes and session length. Additionally, graph attributes such as centrality can be used to identify critical nodes in a network. Finally, many important protocols (in particular, SMTP and routing) rely on algorithms that model their particular network as a graph.
The remainder of this chapter is focused on the analytic properties of graphs. We begin by describing what a graph is and then developing examples for major attributes: shortest paths, centrality, clusters, and clustering coefficient.
Graph Attributes: What Is a Graph?
A graph is a mathematical representation of a collection of objects and their interrelationships. Originally developed in 1736 by Leonhard Euler to address the problem of crossing the bridges of Konigsberg, graphs have since been used to model everything from the core members of conspiracies to the frequency of sounds uttered in the English language. Graphs are an extremely powerful and flexible descriptive tool, and that power comes because they are extremely fungible. Researchers in mathematics, engineering, and sociology have developed an extensive set of constructed and observed ...
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