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Modeling and analyzing malware diffusion in wireless sensor networks based on cellular automaton

Author

Listed:
  • Hong Zhang
  • Shigen Shen
  • Qiying Cao
  • Xiaojun Wu
  • Shaofeng Liu

Abstract

Wireless sensor networks, as a multi-hop self-organized network system formed by wireless communication, are vulnerable to malware diffusion by breaking the data confidentiality and service availability, owing to their low configuration and weak defense mechanism. To reveal the rules of malware diffusion in the really deployed wireless sensor networks, we propose a model called Malware Diffusion Based on Cellular Automaton to describe the dynamics of malware diffusion based on cellular automaton. According to the model, we first analyze and obtain the differential equations, which can reflect the various state dynamics of sensor nodes with cellular automaton. Then, we attain the equilibrium points of the model Malware Diffusion Based on Cellular Automaton to determine the threshold for whether malware will diffuse or die out in wireless sensor networks. Furthermore, we compute the basic regeneration number of the model Malware Diffusion Based on Cellular Automaton using the next-generation matrix and prove the stability of the equilibrium points. Finally, via experimental simulation, we verify the effectiveness of the model Malware Diffusion Based on Cellular Automaton, which can provide administrators with the theoretical guidance on suppressing malware diffusion in wireless sensor networks.

Suggested Citation

  • Hong Zhang & Shigen Shen & Qiying Cao & Xiaojun Wu & Shaofeng Liu, 2020. "Modeling and analyzing malware diffusion in wireless sensor networks based on cellular automaton," International Journal of Distributed Sensor Networks, , vol. 16(11), pages 15501477209, November.
  • Handle: RePEc:sae:intdis:v:16:y:2020:i:11:p:1550147720972944
    DOI: 10.1177/1550147720972944
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    References listed on IDEAS

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    1. Harshita Patel & Dharmendra Singh Rajput & G Thippa Reddy & Celestine Iwendi & Ali Kashif Bashir & Ohyun Jo, 2020. "A review on classification of imbalanced data for wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 16(4), pages 15501477209, April.
    2. Shuguang Deng & Buwen Cao & Xiang Xiao & Hua Qin & Bing Yang, 2020. "Cognitive routing optimization protocol based on multiple channels in wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 16(4), pages 15501477209, April.
    3. Sharma, Natasha & Gupta, Arvind Kumar, 2017. "Impact of time delay on the dynamics of SEIR epidemic model using cellular automata," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 114-125.
    4. Wen Jiang & Zeyu Ma & Xinyang Deng, 2019. "An attack-defense game based reliability analysis approach for wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 15(4), pages 15501477198, April.
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    Cited by:

    1. Min Wei & Chunmeng Rong & Erxiong Liang & Yuan Zhuang, 2022. "An intrusion detection mechanism for IPv6-based wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 18(3), pages 15501329221, March.

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