Complex Sciences. First International Conference, Complex 2009, Shanghai, China, February 23-25, 2009. Revised Papers, Part 1

Research Article

Model and Dynamic Behavior of Malware Propagation over Wireless Sensor Networks

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  • @INPROCEEDINGS{10.1007/978-3-642-02466-5_47,
        author={Yurong Song and Guo-Ping Jiang},
        title={Model and Dynamic Behavior of Malware Propagation over Wireless Sensor Networks},
        proceedings={Complex Sciences. First International Conference, Complex 2009, Shanghai, China, February 23-25, 2009. Revised Papers, Part 1},
        proceedings_a={COMPLEX PART 1},
        year={2012},
        month={5},
        keywords={wireless sensor networks malware propagation model cellular automata neighborhood saturation MAC mechanism theoretical analysis},
        doi={10.1007/978-3-642-02466-5_47}
    }
    
  • Yurong Song
    Guo-Ping Jiang
    Year: 2012
    Model and Dynamic Behavior of Malware Propagation over Wireless Sensor Networks
    COMPLEX PART 1
    Springer
    DOI: 10.1007/978-3-642-02466-5_47
Yurong Song1,*, Guo-Ping Jiang1,*
  • 1: Nanjing University of Posts and Telecommunications
*Contact email: songyr@njupt.edu.cn, jianggp@njupt.edu.cn

Abstract

Based on the inherent characteristics of wireless sensor networks (WSN), the dynamic behavior of malware propagation in flat WSN is analyzed and investigated. A new model is proposed using 2-D cellular automata (CA), which extends the traditional definition of CA and establishes whole transition rules for malware propagation in WSN. Meanwhile, the validations of the model are proved through theoretical analysis and simulations. The theoretical analysis yields closed-form expressions which show good agreement with the simulation results of the proposed model. It is shown that the malware propaga-tion in WSN unfolds neighborhood saturation, which dominates the effects of increasing infectivity and limits the spread of the malware. MAC mechanism of wireless sensor networks greatly slows down the speed of malware propagation and reduces the risk of large-scale malware prevalence in these networks. The proposed model can describe accurately the dynamic behavior of malware propagation over WSN, which can be applied in developing robust and efficient defense system on WSN.