Abstract
Based on the epidemic theory, this paper proposes a novel model for analyzing the dynamics of worm propagation in Wireless Sensor Networks (WSNs). The proposed model supports the sleep and work interleaving schedule policy for sensor nodes, and it can also describe the process of multi-worm propagation in WSNs. In addition, a necessary condition for worms to spread in WSNs is derived, which may be useful in designing a secure WSN. Simulation results show that the process of worm propagation in WSNs is sensitive to the energy consumption of nodes and the sleep and work interleaving schedule policy for nodes. Therefore, this paper provides new insights for the dynamics of worm propagation in WSNs.
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References
Chen ZS, Gao LX, Kwiat K (2003) Modeling the spread of active worms. In: Proceedings of IEEE INFOCOM, pp 1890–1900
Dantu R, Cangussu JW, Patwardhan S (2007) Fast worm containment using feedback control. IEEE Trans Dependable Secure Comput 4(2):119–136
Eugster PT, Guerraoui R, Kermarrec AM, Massoulie L (2004) Epidemic information dissemination in distributed systems. Mathematical modeling in epidemiology. IEEE Comput 37(5):60–67
Frauenthal JC (1981) Mathematical modeling in epidemiology. Springer, New York. ISBN-10:0387103287
Kephart OJ, White RS (1991) Directed-graph epidemiological models of computer viruses. In: Proceedings of IEEE symposium on security and privacy, pp 22–35
Kim J, Radhakrishnan S, Dhall SK (2004) Measurement and analysis of worm propagation on Internet network topology. In: Proceedings of IEEE international conference on computer communications and networks, pp 495–500
Moore D, Paxson V, Savage S, Shannon C, Stanoford S, Weaver N (2003) Inside the slammer worm. IEEE Secur Priv 1(4):33–39
Okamura H, Kobayashi H, Dohi T (2005) Markovian modeling and analysis of Internet worm propagation. In: Proceedings of the 16th IEEE international symposium on soft reliability engineering, pp 149–158
Onwubiko C, Lenaghan AP, Hebbes L (2005) An improved worm mitigation model for evaluating the spread of aggressive network worms. In: Proceedings of IEEE international conference on computer as tool, pp 1710–1713
Pradip D, Liu Y, Sajalk D (2007) Modeling node comprise spread in wireless sensor networks using epidemic theory. In: Proceedings of IEEE international symposium on a world of wireless, mobile and multimedia networks, pp 237–243
Syed KA, Hayder R (2006) Using signal processing techniques to model worm propagation over wireless sensor networks. IEEE Signal Process Mag 23(2):164–169
Wang X, Li Y (2008) A improved SIR model for worm propagation in wireless sensor networks. Chin J Electron 18(1):28–32
Yang F, Duan HX, Li X (2005) Modeling and analyzing of the interaction between worms and antiworms during network worm propagation. Sci China Ser E Inf Sci 34(8):841–856
Zou CC, Gong G, Towsley D (2005) The monitoring and early warning for Internet worms. IEEE Trans Netw 13(6):961–974
Zou CC, Towsley D, Gong W (2007) Modeling and simulation study of the propagation and defense of Internet e-mail worms. IEEE Trans Dependable Secure Comput 4(2):105–118
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X. Wang and Q. Li are supported by NSFC-60773224,10571052, and Key Project of Ministry of Education of China (Grant 107106).
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Wang, X., Li, Q. & Li, Y. EiSIRS: a formal model to analyze the dynamics of worm propagation in wireless sensor networks. J Comb Optim 20, 47–62 (2010). https://doi.org/10.1007/s10878-008-9190-9
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DOI: https://doi.org/10.1007/s10878-008-9190-9