Effects of Resource Limitations and Cost Influences on Computer Virus Epidemic Dynamics and Tipping Points

Chung-Yuan Huang,Chuen-Tsai Sun

doi:10.1155/2012/473136

Abstract

One of the most important assessment indicators of computer virus infections is epidemic tipping point. Although many researchers have focused on the effects of scale-free network power-law connectivity distributions on computer virus epidemic dynamics and tipping points, few have comprehensively considered resource limitations and costs. Our goals for this paper are to show that (a) opposed to the current consensus, a significant epidemic tipping point does exist when resource limitations and costs are considered and (b) it is possible to control the spread of a computer virus in a scale-free network if resources are restricted and if costs associated with infection events are significantly increased.

Highlights

Research on the epidemic dynamics of computer viruses has increasingly incorporated Watts and Strogatz’s 1 description of small-world networks characterized by tightly clustered connections and short paths between node pairs and Barabasi and Albert’s 2 insights regarding scale-free networks marked by power-law connectivity distributions
Our four main findings are as follows a a significant epidemic tipping point exists when resource limitations and costs are taken into consideration, with the tipping point exhibiting a lower bound; b when interaction costs increase or usable resources decrease, epidemic tipping points in scale-free networks grow linearly while steady density curves shrink linearly; c regardless of whether Internet user resources obey delta, uniform, or normal distributions, they retain the same epidemic dynamics and tipping points as long as the average value of those resources remains unchanged across different scale-free networks; d the spread of epidemics in scale-free networks remains controllable as long as resources are properly restricted and intervention strategy investments are significantly increased
In this paper we described five characteristics of network resources and proposed an agent-based epidemic simulation model for investigating how resources and interaction costs influence the epidemic dynamics and tipping points of computer viruses in scale-free networks

Summary

Introduction

Research on the epidemic dynamics of computer viruses has increasingly incorporated Watts and Strogatz’s 1 description of small-world networks characterized by tightly clustered connections and short paths between node pairs and Barabasi and Albert’s 2 insights regarding scale-free networks marked by power-law connectivity distributions. Our four main findings are as follows a a significant epidemic tipping point exists when resource limitations and costs are taken into consideration, with the tipping point exhibiting a lower bound; b when interaction costs increase or usable resources decrease, epidemic tipping points in scale-free networks grow linearly while steady density curves shrink linearly; c regardless of whether Internet user resources obey delta, uniform, or normal distributions, they retain the same epidemic dynamics and tipping points as long as the average value of those resources remains unchanged across different scale-free networks; d the spread of epidemics in scale-free networks remains controllable as long as resources are properly restricted and intervention strategy investments are significantly increased. We believe these conclusions can assist computer scientists in their efforts to understand the epidemic dynamics and tipping points of computer virus infections and to identify potential immunization and virus control strategies 22, 23

Agent-Based Epidemic Simulation Model

Epidemic Model Analysis

Experimental Results

Conclusion