Security Visualization is a subject that broadly covers the aspect of Big Data , Visualization , Human perception and Security . Each day, we are collecting more and more data in the form of data files. Big Data Mining Techniques Like Map Reduce help narrow the search for meaning in data. Data visualization is a data analytics technique, which is used to engage the human brain while finding patterns in data.
Recognition and cognition of patterns will lead to recognition and cognition of anomalous patterns as well. Security Visualization helps a security analyst identify imminent vulnerability and attacks in a network. Simple visualizations like bar charts and pie charts are naive and unintuitive when it comes to Big Data . Special, customized visual techniques such as Choropleth mapand Hive Plot are often desired for effective communication of Big Data . The book “Applied Security Visualization” is an in-depth study of the correlation between Security and Data Visualization. 
Choropleth is a Visualization that depicts the intensity of a quantity through color shading. It may be useful in the areas of interest and safety, which is important to the reader. A Choropleth map is a geographical map in which the counties are shaded to depict region of interest.
Computer Networks are often very troublesome to visualize because of their complicated and difficult to understand. A force diagram that is used to depict a computer network often ends up looking like a ball of hair when the number of nodes is large. Hence, making strengths diagrams unsuitable for unorganized Big Data . A hive plot is considered an improvement to Force-directed graph drawing especially suited for big data. Nodes are arranged along three or more axes and edges between nodes are drawn as Bezier curves. 
A Heat Map is a visual technique similar to the Choropleth Map . However, a heat map is usually used with a normalized heat map function. These maps can be used to identify areas of interest that require attention by varying shades and patterns of Color Gradient .
ELISHA is a visual anomaly detection system. Multiple Origin Autonomous System (MOAS) conflicts in a Border Gateway Protocol network. A MOAS conflict is identified by changes in color of the connected nodes in a BGP network. 
- Jump up^ Marty, Raffael (2008). Applied Security Visualization . Addison-Wesley Professional. Pearson Education . ISBN 0-321-51010-0 .
- Jump up^ Krzywinski, Martin (2011). “Hive Plots – Rational Approach to Visualizing Networks”. Briefings in Bioinformatics. doi : 10.1093 / bib / BBR069 .
- Jump up^ ST Teoh; et al. “ELISHA: A Visual-Based Anomaly Detection System for the BGP Routing Protocol” (PDF) .