Resilience of Networks to Spreading Computer Viruses: Optimal Anti-Virus Deployment (Extended Version)

TL;DR

This paper investigates how optimal deployment of anti-virus software can enhance network resilience against computer viruses by leveraging models that account for node heterogeneity, demonstrating the importance of strategic vaccination for herd immunity.

Contribution

It introduces a model considering network heterogeneity and derives optimal anti-virus deployment strategies to maximize herd immunity and network resilience.

Findings

Optimal strategies significantly outperform naive approaches.

Network heterogeneity critically influences virus spread and control.

Numerical results confirm the effectiveness of the proposed strategies.

Abstract

Deployment of anti-virus software is a common strategy for preventing and controlling the propagation of computer viruses and worms over a computer network. As the deployment of such programs is often limited due to monetary or operational costs, devising optimal strategies for their allocation and deployment can be of high value to the operation, performance, and resilience of the target networks. We study the effects of anti-virus deployment (i.e., "vaccination") strategies on the ability of a network to block the spread of a virus. Such ability is obtained when the network reaches "herd immunity", achieved when a large fraction of the network entities is immune to the infection, which provides protection even for entities which are not immune. We use a model that explicitly accounts for the inherent heterogeneity of network nodes activity and derive optimal strategies for anti-virus deployment. Numerical evaluations demonstrate that the system performance is very sensitive to the chosen strategy, and thus strategies which disregard the heterogeneous spread nature may perform significantly worse relatively to those derived in this work.