Cyberspace is a critical part of our lives. Although we all use cyberspace for work, entertainment, and social life, much of its infrastructure and operation is invisible to us. We spend a big part of our lives in an environment that is almost an essential service but is full of potential dangers: a place where criminals can commit new kinds of crimes, where governments can exert political pressure, and where we can be hurt by the unthinking actions of the bored and careless. Making cyberspace more secure is one of the challenges of our times. This is not only (or perhaps even primarily) a technical challenge. It requires actions by governments and businesses to encourage security whenever possible, and to make sure that their own actions do not undermine it. Unfortunately, many of those in a position to do something about cybersecurity do not have the background to understand the issues fully. Cybersecurity for Everyone will help by describing the issues in a way that is accessible to anyone, but especially those from non-technical backgrounds.

High-dimensional spaces arise as a way of modelling datasets with many attributes. Such a dataset can be directly represented in a space spanned by its attributes, with each record represented as a point in the space with its position depending on its attribute values. Such spaces are not easy to work with because of their high dimensionality: our intuition about space is not reliable, and measures such as distance do not provide as clear information as we might expect.

There are three main areas where complex high dimensionality and large datasets arise naturally: data collected by online retailers, preference sites, and social media sites, and customer relationship databases, where there are large but sparse records available for each individual; data derived from text and speech, where the attributes are words and so the corresponding datasets are wide, and sparse; and data collected for security, defense, law enforcement, and intelligence purposes, where the datasets are large and wide. Such datasets are usually understood either by finding the set of clusters they contain or by looking for the outliers, but these strategies conceal subtleties that are often ignored. In this book the author suggests new ways of thinking about high-dimensional spaces using two models: a skeleton that relates the clusters to one another; and boundaries in the empty space between clusters that provide new perspectives on outliers and on outlying regions.

The book will be of value to practitioners, graduate students and researchers."

This book shows how open source intelligence can be a powerful tool for combating crime by linking local and global patterns to help understand how criminal activities are connected. Readers will encounter the latest advances in cutting-edge data mining, machine learning and predictive analytics combined with natural language processing and social network analysis to detect, disrupt, and neutralize cyber and physical threats. Chapters contain state-of-the-art social media analytics and open source intelligence research trends. This multidisciplinary volume will appeal to students, researchers, and professionals working in the fields of open source intelligence, cyber crime and social network analytics. Chapter Automated Text Analysis for Intelligence Purposes: A Psychological Operations Case Study is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book shows how open source intelligence can be a powerful tool for combating crime by linking local and global patterns to help understand how criminal activities are connected. Readers will encounter the latest advances in cutting-edge data mining, machine learning and predictive analytics combined with natural language processing and social network analysis to detect, disrupt, and neutralize cyber and physical threats. Chapters contain state-of-the-art social media analytics and open source intelligence research trends. This multidisciplinary volume will appeal to students, researchers, and professionals working in the fields of open source intelligence, cyber crime and social network analytics. Chapter Automated Text Analysis for Intelligence Purposes: A Psychological Operations Case Study is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Cyberspace is a critical part of our lives. Although we all use cyberspace for work, entertainment, and social life, much of its infrastructure and operation is invisible to us. We spend a big part of our lives in an environment that is almost an essential service but is full of potential dangers: a place where criminals can commit new kinds of crimes, where governments can exert political pressure, and where we can be hurt by the unthinking actions of the bored and careless. Making cyberspace more secure is one of the challenges of our times. This is not only (or perhaps even primarily) a technical challenge. It requires actions by governments and businesses to encourage security whenever possible, and to make sure that their own actions do not undermine it. Unfortunately, many of those in a position to do something about cybersecurity do not have the background to understand the issues fully. Cybersecurity for Everyone will help by describing the issues in a way that is accessible to anyone, but especially those from non-technical backgrounds.