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

Guiyun Liu, Baihao Peng, Xiaojing Zhong, Lefeng Cheng and Zhifu Li

Complexity, 2020, vol. 2020, 1-19

Abstract:

As energy-harvesting wireless sensor networks (EHWSNs) are increasingly integrated with all walks of life, their security problems have gradually become hot issues. As an attack means, malicious programs often attack sensor nodes in critical locations in the networks to cause paralysis and information leakage of the networks, resulting in security risks. Based on the previous works and the introduction of solar charging, we proposed a novel model, namely, Susceptible-Infected-Low (energy)-Recovered-Dead (SILRD) with solar energy harvesters. Meanwhile, this paper takes Logistic Growth as the drop rate of sensor nodes and the infection rate of multitype malicious programs under nonlinear condition into consideration. Finally, an - Susceptible-Infected-Low (energy)-Recovered-Dead ( SILRD) model is proposed. Based on the Pontryagin Maximum Principle, this paper proposes the optimal strategies based on the SILRD with solar energy harvesters and the SILRD. The effectiveness of SILRD with solar energy harvesters was demonstrated by comparison with the general epidemic model. At the same time, by analyzing different charging strategies, we conclude that solar charging is highly efficient. Moreover, we further analyze the influence of controllable and uncontrollable input and various node degrees on SILRD model.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:3680518

DOI: 10.1155/2020/3680518

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