Virus and Warning Spread in Dynamical Networks

TL;DR

This paper models virus and warning message spread in dynamic networks using nonlinear dynamical systems theory to understand infection propagation and control mechanisms.

Contribution

It applies classical dynamical systems results to model and analyze the spread of viruses and warnings in networks, advancing understanding of containment strategies.

Findings

Model captures virus and warning dynamics in networks

Provides conditions for infection containment

Suggests strategies for controlling spread

Abstract

Recent work on information survival in sensor and human P2P networks, try to study the datum preservation or the virus spreading in a network under the dynamical system approach. Some interesting solutions propose to use non-linear dynamical systems and fixed point stability theorems, providing closed form formulas that depend on the largest eigenvalue of the dynamic system matrix. Given that in a the Web there can be messages from one place to another, and that this messages can be, with some probability, new unclassified virus warning messages as well as worms or other kind of virus, the sites can be infected very fast. The question to answer is how and when a network infection can become global and how it can be controlled or at least how to stabilize his spreading in such a way that it becomes confined below a fixed portion of the network. In this paper, we try to make a step ahead in this direction and apply classic results of the dynamical systems theory to model the behaviour of a network where warning messages and virus spread.