Dynamics on Hybrid Complex Network: Botnet Modeling and Analysis of Medical IoT

Abstract EN

With the rapid development of Internet of things technology, the application of intelligent devices in the medical industry has become ubiquitous.

Connected devices have revolutionized clinicians and patient care but also made modern hospitals vulnerable to cyber attacks.

Among the security risks, botnets are of particular concern, which can be used to control thousands of devices for remote data theft and equipment destruction.

In this paper, we propose a non-Markovian spread dynamics model to understand the effects of botnet propagation, which can characterize the hybrid contagion situation in reality.

Based on the Susceptible-Adopted-Recovered model, we introduce nonredundant memory spread mechanism for global propagation, as a tuner to adjust spreading rate difference.

For describing the proposed model, we extend a heterogeneous edge-based compartmental theory.

Through extensive numerical simulations, we reveal that the growth pattern of the final adoption size versus the information transmission probability is discontinuous and how the final adoption size is affected by hybrid ratio α, global scope control factor ϵ, accumulated received information threshold T, and other parameters on ER network.

Furthermore, we give the theory and simulation result on BA network and also compare the two hybrid methods—single infection in one time slice and double infections in one time slice—to evaluate the influence on final adoption size.

We found in SIOT hybrid contagion scenario the final adoption size shows the phenomenon of a decline followed by an increase versus different hybrid ratio, and it is both verified in theory and numerical simulation.

Through validation by thousands of experiments, our developed theory agrees well with the numerical simulations.