Dynamics of Botnet Propagation in Software Defined Networks Using Epidemic Models

During COVID-19 the new normal became an increased reliance on remote connectivity, and that fact is far away to change any time soon. The increasing number of networked devices connected Internet causing exponential growth botnets. Subsequently, DDoS (Distributed Denial Service) attacks registered around world also increased, especially during pandemic lockdown. Therefore, it crucial understand how botnets are formed bots propagate within networks. In particular, analytic modelling epidemic process essential component for understanding attacks, thus mitigate their impact. this paper, we propose two models; (i) first one enterprise Software Define Networks (SDN) based SEIRS (Susceptible - Exposed Infected Recovered) approach, while (ii) second model designed service providers’ SDN, a novel extension SEIRS-SEIRS vector-borne approach. Both models illustrate spread in different types SDN We found bot infection behaves similar way human epidemics, such as outbreak. present calculation basic reproduction $R_{\mathrm {o}}$ both test system stability using next generation matrix have validated final value theorem (FVT), with which can determine steady-state values provide better propagation process.