How Socio-economic Factors Affect Regional Malware Rates

Over the past several years I have had the opportunity to talk to customers and governments all over the world about the threat landscape and the data we publish in the Microsoft Security Intelligence Report (SIR).  During these conversations regional malware infection rates always garner a lot of discussion. One of the most interesting questions I’m increasingly asked is what factors contribute to the differences in regional malware infection rates? Or what do regions with low malware infection rates do differently than regions with high malware infection rates? Our Special Edition Microsoft Security Intelligence Report: Linking Cybersecurity Policy and Performance released today provides a new body of research that speaks to these questions.
This study was conducted by Trustworthy Computing’s Global Security Strategy and Diplomacy team    and examines the relationships that a number of different socio-economic factors have with regional malware infection rates across 105 countries.  The study started with a list of 80 factors that was trimmed down to the 34 factors that had a potential correlation with malware infection rates or computers cleaned per mille (CCM).  These factors include such indicators as GDP per capita, broadband penetration, use of mobile devices, Facebook usage, and thirty others.  To provide you with an example, Figure 2 illustrates some of the factors examined in the United States.
 
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