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Computer malware and biological pathogens often use similar mechanisms ofinfections. For this reason, it has been suggested to model malware spreadusing epidemiological models developed to characterize the spread of biologicalpathogens. However, most work examining the similarities between malware andpathogens using such methods was based on theoretical analysis and simulation.  Here we extend the classical Susceptible-Infected-Recovered (SIR)epidemiological model to describe two of the most common infection methods usedby malware. We fit the proposed model to malware collected over a period of oneyear from a major anti-malware vendor. We show that by fitting the proposedmodel it is possible to identify the method of transmission used by themalware, its rate of infection, and the number of machines which will beinfected unless blocked by anti-virus software. The Spearman correlationbetween the number of actual and predicted infected machines is 0.84.  Examining cases where an anti-malware "signature" was transmitted tosusceptible computers by the anti-virus provider, we show that the time toremove the malware will be short and independent of the number of infectedcomputers if fewer than approximately 60% of susceptible computers have beeninfected. If more computers were infected, the time to removal will beapproximately 3.2 greater, and will depend on the fraction of infectedcomputers.  Our results show that the application of epidemiological models of infectionto malware can provide anti-virus providers with information on malware spreadand its potential damage. We further propose that similarities between computermalware and biological pathogens, the availability of data on the former andthe dearth of data on the latter, make malware an extremely useful model fortesting interventions which could later be applied to improve medicine.

Modeling infection methods of computer malware in the presence of vaccinations using epidemiological models: An analysis of real-world data