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Wireless Internet. 15th EAI International Conference, WiCON 2022, Virtual Event, November 2022, Proceedings

Research Article

Learning the Propagation of Worms in Wireless Sensor Networks

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-27041-3_8,
        author={Yifan Wang and Siqi Wang and Guangmo Tong},
        title={Learning the Propagation of Worms in Wireless Sensor Networks},
        proceedings={Wireless Internet. 15th EAI International Conference, WiCON 2022, Virtual Event, November 2022, Proceedings},
        proceedings_a={WICON},
        year={2023},
        month={2},
        keywords={Wireless sensor network Multi-worm propagation Complex neural network},
        doi={10.1007/978-3-031-27041-3_8}
    }
    
  • Yifan Wang
    Siqi Wang
    Guangmo Tong
    Year: 2023
    Learning the Propagation of Worms in Wireless Sensor Networks
    WICON
    Springer
    DOI: 10.1007/978-3-031-27041-3_8
Yifan Wang1,*, Siqi Wang1, Guangmo Tong1
  • 1: University of Delaware, Newark
*Contact email: yifanw@udel.edu

Abstract

Wireless sensor networks (WSNs) are composed of spatially distributed sensors and are considered vulnerable to attacks by worms and their variants. Due to the distinct strategies of worms propagation, the dynamic behavior varies depending on the different features of the sensors. Modeling the spread of worms can help us understand the worm attack behaviors and analyze the propagation procedure. In this paper, we design a communication model under various worms. We aim to learn our proposed model to analytically derive the dynamics of competitive worms propagation. We develop a new searching space combined with complex neural network models. Furthermore, the experiment results verified our analysis and demonstrated the performance of our proposed learning algorithms.

Keywords
Wireless sensor network Multi-worm propagation Complex neural network
Published
2023-02-18
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-27041-3_8
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