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基于攻防博弈模型的无线可充电传感器网络的疫情分析。

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

机构信息

School of Mechanical and Electric Engineering, Guangzhou University, Guangzhou 510006, China.

School of Electronics and Communication Engineering, Guangzhou University, Guangzhou 510006, China.

出版信息

Sensors (Basel). 2021 Jan 15;21(2):594. doi: 10.3390/s21020594.

Abstract

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.

摘要

能量约束阻碍了无线传感器网络(WSNs)的普及和发展。作为一种配备可充电电池的新兴技术,无线可充电传感器网络(WRSNs)正被广泛接受和认可。在本文中,我们研究了 WRSNs 中急需解决的安全问题。在建模中考虑了充电过程、激活反恶意软件程序过程和发起恶意攻击过程后,提出了易感感染抗恶意软件低能量易感(SIALS)模型。通过流行病动力学方法,本文分析了 SIALS 模型的局部和全局稳定性。此外,本文还引入了一个五元攻击-防御博弈模型,以进一步研究恶意软件和 WRSNs 之间的动态关系。通过引入成本函数并构建哈密顿函数,基于庞特里亚金极大值原理得到了恶意软件和 WRSNs 的最优策略。此外,仿真结果验证了所提出理论的有效性,并揭示了参数对感染的影响。具体来说,应用前向后向扫掠法解决了伴随变量在终端时刻收敛的问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc85/7830907/ce62ff63e07b/sensors-21-00594-g001.jpg

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