An Epidemiology-Based Model for Disclosing Dynamics of Malware Propagation in Heterogeneous and Mobile WSNs

Abstract

Heterogeneous and mobile wireless sensor networks (HMWSNs) are generally practical in constructing smart Internet of Things. However, malware can easily propagate itself over HMWSNs and make harm such as data interception and unauthorized activities. To defend such malware, developing a model to disclose dynamics of malware propagation becomes urgently required. In this context, a heterogeneous and mobile vulnerable-compromised-quarantined-patched-scrapped (VCQPS) model is proposed by considering both the heterogeneity and mobility of HMSNs (heterogeneous and mobile sensor nodes). Then, differential equations of transition proportions among all states are achieved by analyzing the changeable quantities of HMSNs belonging to different states. Further, the existence of the stationary points of the VCQPS model is proved, upon which the malware propagation threshold is derived by calculating the reproduction number. The stability of the malware-free stationary-point is also proved. Experiments are performed to validate the stability of the malware-free stationary-point and show the effectiveness of the VCQPS model by comparing our model with traditional SIS and SIR models.INDEX TERMS Heterogeneous and mobile wireless sensor networks, malware, epidemic theory, heterogeneity, mobility.

Dynamical Analysis and Optimal Control for a SEIR Model Based on Virus Mutation in WSNs

“…In addition, they obtained the sufficient conditions for the local stability and the existence of Hopf bifurcation. In addition, a variety of models have been proposed, such as SILRD [30], I2S2R [31], SEIQRV [32], VCQPS [33], etc.…”

SIR1R2: Characterizing Malware Propagation in WSNs With Second Immunization

“…Muthukrishnan et al [39] gave a WSNs nodebased epidemic SITPS model including states Susceptible, Infectious, Traced, Patched, and Susceptible. Other typical models consist of an SEIRS-V [40] model introducing V (Vaccination) into the SEIR model, an SEIRS-V model considering the factor of software diversity [41], a VCQPS model reflecting both the heterogeneity and mobility of SNs [42], an epidemic SEIQRV model aggregating quarantine and vaccination techniques [43], a general SEIR model with vaccination-based sliding control [44], an SIC model reflecting countermeasure and network topology [45], an SIQVD model based on time delay and changeable infection probability [46], an SIR-based containment model with mobile social IoT [47], an SEIRD model with Cellular Automaton [48], as well as an SEIRS-V model considering the impact of mobile devices [49].…”

Dynamics of Botnet Propagation in Software Defined Networks Using Epidemic Models

“…However, the model does not consider the chance of the nodes being infected again after the malware is removed which is possible as we already stated. Models developed for specific scenarios and environments can be also found for mobile wireless sensors networks (WSN) [19], [20], [35], [36]; mobile devices [21], [37]; social networks [22], [38]; IoT networks [23]; industrial control system (ICS) networks [24].…”