Attack-Defense Game between Malicious Programs and Energy-Harvesting Wireless Sensor Networks Based on Epidemic Modeling

Peng

Liang

et al. 2021

Entropy

Self Cite

Virus spreading problems in wireless rechargeable sensor networks (WSNs) are becoming a hot topic, and the problem has been studied and discussed in recent years. Many epidemic spreading models have been introduced for revealing how a virus spreads and how a virus is suppressed. However, most of them assumed the sensors are not rechargeable sensors. In addition, most of existing works do not consider virus mutation problems. This paper proposes a novel epidemic model, including susceptible, infected, variant, low-energy and dead states, which considers the rechargeable sensors and the virus mutation factor. The stability of the proposed model is first analyzed by adopting the characteristic equation and constructing Lyapunov functions methods. Then, an optimal control problem is formulated to control the virus spread and decrease the cost of the networks by applying Pontryagin’s maximum principle. Finally, all of the theoretical results are confirmed by numerical simulation.

Section: Related Workmentioning

confidence: 99%

Dynamics Analysis of a Wireless Rechargeable Sensor Network for Virus Mutation Spreading

Peng

Liang

et al. 2021

Entropy

Self Cite

“…However, we know that the time delay of the charging process in WRSNs has not been investigated previously. This paper mainly provides a kind of influence on time delay based on the SIS model combined with low-energy nodes (L) [23][24][25]. Thus, a novel epidemic model (1) of virus spreading in WRSNs is developed.…”

Section: Time Delay Of the Incubationmentioning

confidence: 99%

Analysis of Time-Delay Epidemic Model in Rechargeable Wireless Sensor Networks

Liang

et al. 2021

Mathematics

Self Cite

With the development of wireless rechargeable sensor networks (WRSNs), many scholars began to attach attention to network security under the spread of viruses. This paper mainly studies a novel low-energy-status-based model SISL (Susceptible, Infected, Susceptible, Low-Energy). The conversion process from low-energy nodes to susceptible nodes is called charging. It is noted that the time delay of the charging process in WRSNs should be considered. However, the charging process and its time delay have not been investigated in traditional epidemic models in WRSNs. Thus, the model SISL is proposed. The basic reproduction number, the disease-free equilibrium point, and the endemic equilibrium point are discussed here. Meanwhile, local stability and global stability of the disease-free equilibrium point and the endemic equilibrium point are analyzed. The addition of the time-delay term needs to be analyzed to determine whether it affects the stability. The intervention treatment strategy under the optimal control is obtained through the establishment of the Hamiltonian function and the application of the Pontryagin principle. Finally, the theoretical results are verified by simulations.

“…Based on the previous works [ 41 ] and inspired by [ 23 ], this paper proposes an epidemic model that includes the anti-malware (A) state, constructs game between malware and WRSNs, and obtains the optimal control strategies for both parties.…”

Section: Introductionmentioning

confidence: 99%

Epidemic Analysis of Wireless Rechargeable Sensor Networks Based on an Attack–Defense Game Model

Peng

Zhong

2021

Sensors

Self Cite

Energy constraint hinders the popularization and development of wireless sensor networks (WSNs). As an emerging technology equipped with rechargeable batteries, wireless rechargeable sensor networks (WRSNs) are being widely accepted and recognized. In this paper, we research the security issues in WRSNs which need to be addressed urgently. After considering the charging process, the activating anti-malware program process, and the launching malicious attack process in the modeling, the susceptible–infected–anti-malware–low-energy–susceptible (SIALS) model is proposed. Through the method of epidemic dynamics, this paper analyzes the local and global stabilities of the SIALS model. Besides, this paper introduces a five-tuple attack–defense game model to further study the dynamic relationship between malware and WRSNs. By introducing a cost function and constructing a Hamiltonian function, the optimal strategies for malware and WRSNs are obtained based on the Pontryagin Maximum Principle. Furthermore, the simulation results show the validation of the proposed theories and reveal the influence of parameters on the infection. In detail, the Forward–Backward Sweep method is applied to solve the issues of convergence of co-state variables at terminal moment.