Security visualisation is a subject that broadly covers aspects of big data, visualisation, human perception and security. Each day, we are collecting more and more data in the form of log files and it is often meaningless if the data is not analyzed thoroughly. Big data mining techniques like Map Reduce help narrow down the search for meaning in vast data. Data visualisation is a data analytics technique, which is used to engage the human brain into finding patterns in data.
Recognition and cognition of patterns will also lead to the identification of anomalous patterns. Security visualisation helps a security analyst identify imminent vulnerability and attacks in a network. Simple visualisations like bar charts and pie charts are naïve and unintuitive when it comes to big data. Special, customized visual techniques like a choropleth map and hive plot are often desired for effective communication of big data. The book Applied Security Visualisation is an in-depth study of the correlation between Security and Data Visualisation. [1]
Choropleth is a visualization that depicts the intensity of a quantity through color shading. It can be useful in finding areas of interest through the variations in color and therefore a human readers attention will be drawn to the area that requires security attention. A Choropleth map is a geographical map in which the states or counties are shaded to depict region of interest.
Computer networks are often very troublesome to visualize because they end up looking 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 force diagrams unsuitable for unorganised 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 Bézier curves. [2]
A heatmap is a visual technique similar to the choropleth map. However, a heatmap is shaded with gradient colors, which are usually computed using a normalized heatmap function. These maps can be used to recognize areas that require attention through varying shades and patterns of color gradient.
ELISHA is a visual anomaly detection system. The tool aims at identifying 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. [3]
Network mapping is the study of the physical connectivity of networks e.g. the Internet. Network mapping discovers the devices on the network and their connectivity. It is not to be confused with network discovery or network enumeration which discovers devices on the network and their characteristics such as operating system, open ports, listening network services, etc. The field of automated network mapping has taken on greater importance as networks become more dynamic and complex in nature.
Scientific visualization is an interdisciplinary branch of science concerned with the visualization of scientific phenomena. It is also considered a subset of computer graphics, a branch of computer science. The purpose of scientific visualization is to graphically illustrate scientific data to enable scientists to understand, illustrate, and glean insight from their data. Research into how people read and misread various types of visualizations is helping to determine what types and features of visualizations are most understandable and effective in conveying information.
Visualization, also known as Graphics Visualization, is any technique for creating images, diagrams, or animations to communicate a message. Visualization through visual imagery has been an effective way to communicate both abstract and concrete ideas since the dawn of humanity. from history include cave paintings, Egyptian hieroglyphs, Greek geometry, and Leonardo da Vinci's revolutionary methods of technical drawing for engineering purposes that actively involve scientific requirements.
False colors and pseudo colors respectively refers to a group of color rendering methods used to display images in colors which were recorded in the visible or non-visible parts of the electromagnetic spectrum. A false-color image is an image that depicts an object in colors that differ from those a photograph would show. In this image, colors have been assigned to three different wavelengths that human eyes cannot normally see.
Infographic are graphic visual representations of information, data, or knowledge intended to present information quickly and clearly. They can improve cognition by using graphics to enhance the human visual system's ability to see patterns and trends. Similar pursuits are information visualization, data visualization, statistical graphics, information design, or information architecture. Infographics have evolved in recent years to be for mass communication, and thus are designed with fewer assumptions about the readers' knowledge base than other types of visualizations. Isotypes are an early example of infographics conveying information quickly and easily to the masses.
A choropleth map is a type of statistical thematic map that uses pseudocolor, meaning color corresponding with an aggregate summary of a geographic characteristic within spatial enumeration units, such as population density or per-capita income.
In color theory, a color scheme is a combination of 2 or more colors used in aesthetic or practical design. Aesthetic color schemes are used to create style and appeal. Colors that create a harmonious feeling when viewed together are often used together in aesthetic color schemes. Practical color schemes are used to inhibit or facilitate color tasks, such as camouflage color schemes or high visibility color schemes. Qualitative and quantitative color schemes are used to encode unordered categorical data and ordered data, respectively. Color schemes are often described in terms of logical combinations of colors on a color wheel or within a color space.
Software visualization or software visualisation refers to the visualization of information of and related to software systems—either the architecture of its source code or metrics of their runtime behavior—and their development process by means of static, interactive or animated 2-D or 3-D visual representations of their structure, execution, behavior, and evolution.
Data and information visualization is the practice of designing and creating easy-to-communicate and easy-to-understand graphic or visual representations of a large amount of complex quantitative and qualitative data and information with the help of static, dynamic or interactive visual items. Typically based on data and information collected from a certain domain of expertise, these visualizations are intended for a broader audience to help them visually explore and discover, quickly understand, interpret and gain important insights into otherwise difficult-to-identify structures, relationships, correlations, local and global patterns, trends, variations, constancy, clusters, outliers and unusual groupings within data. When intended for the general public to convey a concise version of known, specific information in a clear and engaging manner, it is typically called information graphics.
A heat map is a 2-dimensional data visualization technique that represents the magnitude of individual values within a dataset as a color. The variation in color may be by hue or intensity.
In cartographic design, map coloring is the act of choosing colors as a form of map symbol to be used on a map.
A thematic map is a type of map that portrays the geographic pattern of a particular subject matter (theme) in a geographic area. This usually involves the use of map symbols to visualize selected properties of geographic features that are not naturally visible, such as temperature, language, or population. In this, they contrast with general reference maps, which focus on the location of a diverse set of physical features, such as rivers, roads, and buildings. Alternative names have been suggested for this class, such as special-subject or special-purpose maps, statistical maps, or distribution maps, but these have generally fallen out of common usage. Thematic mapping is closely allied with the field of Geovisualization.
A bivariate map or multivariate map is a type of thematic map that displays two or more variables on a single map by combining different sets of symbols. Each of the variables is represented using a standard thematic map technique, such as choropleth, cartogram, or proportional symbols. They may be the same type or different types, and they may be on separate layers of the map, or they may be combined into a single multivariate symbol.
Biological data visualization is a branch of bioinformatics concerned with the application of computer graphics, scientific visualization, and information visualization to different areas of the life sciences. This includes visualization of sequences, genomes, alignments, phylogenies, macromolecular structures, systems biology, microscopy, and magnetic resonance imaging data. Software tools used for visualizing biological data range from simple, standalone programs to complex, integrated systems.
A dot distribution map is a type of thematic map that uses a point symbol to visualize the geographic distribution of a large number of related phenomena. Dot maps are a type of unit visualizations that rely on a visual scatter to show spatial patterns, especially variances in density. The dots may represent the actual locations of individual phenomena, or be randomly placed in aggregation districts to represent a number of individuals. Although these two procedures, and their underlying models, are very different, the general effect is the same.
Targeted projection pursuit is a type of statistical technique used for exploratory data analysis, information visualization, and feature selection. It allows the user to interactively explore very complex data to find features or patterns of potential interest.
BioFabric is an open-source software application for graph drawing. It presents graphs as a node-link diagram, but unlike other graph drawing tools that depict the nodes using discrete symbols, it represents nodes using horizontal lines.
A visual variable, in cartographic design, graphic design, and data visualization, is an aspect of a graphical object that can visually differentiate it from other objects, and can be controlled during the design process. The concept was first systematized by Jacques Bertin, a French cartographer and graphic designer, and published in his 1967 book, Sémiologie Graphique. Bertin identified a basic set of these variables and provided guidance for their usage; the concept and the set of variables has since been expanded, especially in cartography, where it has become a core principle of education and practice.
Cartographic design or map design is the process of crafting the appearance of a map, applying the principles of design and knowledge of how maps are used to create a map that has both aesthetic appeal and practical function. It shares this dual goal with almost all forms of design; it also shares with other design, especially graphic design, the three skill sets of artistic talent, scientific reasoning, and technology. As a discipline, it integrates design, geography, and geographic information science.