This paper describes the utilization of an epidemic approach to study the propagation of jamming attacks,
which can affect to different communication layers of all nodes in a variety of Internet of Things (IoT) wireless
networks, regardless of the complexity and computing power of the devices. The jamming term considers both the
more classical approach of interfering signals focusing on the physical level of the systems, and the cybersecurity
approach that includes the attacks generated in upper layers like Medium Access Control (MAC), producing the same
effect on the communication channel. In order to study the accuracy of the proposed epidemic model to estimate the
propagation of jamming attacks, this paper uses the results of public simulations and experiments. It is of special
interest the data obtained from experiments based on protocols such as Multi-Parent Hierarchical Protocol (MPH),
Ad-hoc On-demand Distance Vector (AODV), and Dynamic Source Routing (DSR), working over the IEEE 802.15.4
standard. Then, using the formulation of the deterministic epidemiological model Susceptible–Infected–Recovered
(SIR), together the abovementioned simulation, it has been seen that the proposed epidemic model could be used to
estimate in that kind of IoT networks, the impact of the jamming attack in terms of attack severity and attack
persistence
