Lévy impact on the transmission of worms in wireless sensor network: Stochastic analysis
This manuscript addresses the security challenges wireless sensor networks (WSNs) face due to their operational limitations. The primary challenge stems from the infiltration of worms into the network, where one infected node could uncontrollably propagate the malware to neighboring node(s). First,...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-09-01
|
| Series: | Results in Physics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2211379723005508 |
| _version_ | 1797682901931786240 |
|---|---|
| author | Qi Liu Aeshah A. Raezah Anwarud Din |
| author_facet | Qi Liu Aeshah A. Raezah Anwarud Din |
| author_sort | Qi Liu |
| collection | DOAJ |
| description | This manuscript addresses the security challenges wireless sensor networks (WSNs) face due to their operational limitations. The primary challenge stems from the infiltration of worms into the network, where one infected node could uncontrollably propagate the malware to neighboring node(s). First, we proposes a stochastic system based on Lévy noise to explain the spread of worms in WSNs. Then, we establish a unique positive global solution for the proposed model. We also examine the presence and potential extinction of worms within the networks. The results reveal that random environmental perturbations can confine the spread of worms and that the deterministic model tends to overestimate the worms’ spreading capacity. Using different parameter sets, the study obtains approximate solutions to validate these analytical findings and demonstrate the effectiveness of the suggested SEIRS system. The findings of the work reveal that the proposed model surpasses existing models in mitigating worm transmission in WSNs. Our inference suggests that the transmission dynamics of the system are influenced by both white noise and Lévy noise. |
| first_indexed | 2024-03-12T00:06:38Z |
| format | Article |
| id | doaj.art-e1d907fc87984a759c211c8a3978fc89 |
| institution | Directory Open Access Journal |
| issn | 2211-3797 |
| language | English |
| last_indexed | 2024-03-12T00:06:38Z |
| publishDate | 2023-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Physics |
| spelling | doaj.art-e1d907fc87984a759c211c8a3978fc892023-09-17T04:56:08ZengElsevierResults in Physics2211-37972023-09-0152106757Lévy impact on the transmission of worms in wireless sensor network: Stochastic analysisQi Liu0Aeshah A. Raezah1Anwarud Din2School of Mathematics and Physics, Anqing Normal University, Anqing 246001, PR ChinaDepartment of Mathematics, Faculty of Science, King Khalid University, Abha 62529, Saudi Arabia; Corresponding author.Department of Mathematics, Sun Yat-sen University, Guangzhou 510275, PR ChinaThis manuscript addresses the security challenges wireless sensor networks (WSNs) face due to their operational limitations. The primary challenge stems from the infiltration of worms into the network, where one infected node could uncontrollably propagate the malware to neighboring node(s). First, we proposes a stochastic system based on Lévy noise to explain the spread of worms in WSNs. Then, we establish a unique positive global solution for the proposed model. We also examine the presence and potential extinction of worms within the networks. The results reveal that random environmental perturbations can confine the spread of worms and that the deterministic model tends to overestimate the worms’ spreading capacity. Using different parameter sets, the study obtains approximate solutions to validate these analytical findings and demonstrate the effectiveness of the suggested SEIRS system. The findings of the work reveal that the proposed model surpasses existing models in mitigating worm transmission in WSNs. Our inference suggests that the transmission dynamics of the system are influenced by both white noise and Lévy noise.http://www.sciencedirect.com/science/article/pii/S2211379723005508Sensor networksStochastic epidemic modelLévy jumpPersistencePerformance analysis |
| spellingShingle | Qi Liu Aeshah A. Raezah Anwarud Din Lévy impact on the transmission of worms in wireless sensor network: Stochastic analysis Results in Physics Sensor networks Stochastic epidemic model Lévy jump Persistence Performance analysis |
| title | Lévy impact on the transmission of worms in wireless sensor network: Stochastic analysis |
| title_full | Lévy impact on the transmission of worms in wireless sensor network: Stochastic analysis |
| title_fullStr | Lévy impact on the transmission of worms in wireless sensor network: Stochastic analysis |
| title_full_unstemmed | Lévy impact on the transmission of worms in wireless sensor network: Stochastic analysis |
| title_short | Lévy impact on the transmission of worms in wireless sensor network: Stochastic analysis |
| title_sort | levy impact on the transmission of worms in wireless sensor network stochastic analysis |
| topic | Sensor networks Stochastic epidemic model Lévy jump Persistence Performance analysis |
| url | http://www.sciencedirect.com/science/article/pii/S2211379723005508 |
| work_keys_str_mv | AT qiliu levyimpactonthetransmissionofwormsinwirelesssensornetworkstochasticanalysis AT aeshaharaezah levyimpactonthetransmissionofwormsinwirelesssensornetworkstochasticanalysis AT anwaruddin levyimpactonthetransmissionofwormsinwirelesssensornetworkstochasticanalysis |