Journal article Open Access

Cyber Crime Nation Typologies: K-Means Clustering of Countries Based on Cyber Crime Rates

Kigerl, Alex

Editor(s)
K Jaishankar

Cyber crime is a worldwide problem, with a global reach. Cyber crimes do not respect national boundaries, and so can be sent to and from anywhere in the world. Many reports, mostly by cyber security firms, regularly release information ranking the different nations in terms of top cyber crime output, broken down into varying cyber crime types. However, little has been done to classify nations according to separate cyber crime typologies using any multivariate methods. Instead, reporting is descriptive and unidimensional.  The present research sought to fill this gap by conducting K-means clustering analysis on a sample of 190 countries using seven dimensions of cyber crime ranging from malware, fraud, spam, and digital piracy, as well as measures of GDP and internet use. The findings determined that nations can be broken down into four distinct categories based on cyber crime activity: low cyber crime countries, non-serious cyber crime countries, advance fee fraud countries, and phishing scam countries. The implications of these findings and the directions for future research are discussed.

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