Abstract
Malware is a potential vulnerability for the Internet of Things; it is for this reason that spread of malware on Wireless Sensor Networks has been studied from different perspectives. However, the individual characteristics have not been considered in most of the proposed models. Consequently, Agent-Based Models can be used, as a mathematical tool, to analyse malware propagation. In this work, an ABM is created from three main elements: agents, environment and rules. This article presents a review of an agent-based model to simulate malware spreading in wireless sensor networks.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Abar, S., Theodoropoulos, G.K., Lemarinier, P., O’Hare, G.M.: Agent based modelling and simulation tools: a review of the state-of-art software. Comput. Sci. Rev. 24, 13–33 (2017)
Anderson, T.M., Dragićević, S.: Network-agent based model for simulating the dynamic spatial network structure of complex ecological systems. Ecol. Modell. 389, 19–32 (2018)
Arifin, S.N., Madey, G.R., Collins, F.H.: Spatial Agent-Based Simulation Modeling in Public Health: Design, Implementation, and Applications for Malaria Epidemiology. Wiley, New York (2016)
Bin Karnain, A., Bin Zakaria, Z.: A review on ZigBee security enhancement in smart home environment. In: 2nd International Conference on Information Science and Security (ICISS), pp. 1–4. IEEE (2015)
Chizari, H., Zulkurnain, A.U.: Modelling malware response in wireless sensor networks using stochastic cellular automata. J. Mobile Embed. Distrib. Syst. 6(4), 159–166 (2014)
Chu, Z., Yang, B., Ha, C.Y., Ahn, K.: Modeling GDP fluctuations with agent-based model. Physica A 503, 572–581 (2018)
Conti, M.: Secure Wireless Sensor Networks: Threats and Solutions, vol. 65. Springer, New York (2015)
Feng, L., Song, L., Zhao, Q., Wang, H.: Modeling and stability analysis of worm propagation in wireless sensor network. Math. Probl. Eng. (2015)
Helbing, D.: Social Self-Organization: Agent-Based Simulations and Experiments to Study Emergent Social Behavior. Springer, Heidelberg (2012)
Hu, J., Song, Y.: The model of malware propagation in wireless sensor networks with regional detection mechanism. In: China Conference on Wireless Sensor Networks, pp. 651–662. Springer (2014)
Kermack, W.O., Mckendrick, A.G.: A contribution to the mathematical theory of epidemics. Proc. R. Soc. Lond. 115, 700–721 (1927)
Keshri, N., Mishra, B.K.: Optimal control model for attack of worms in wireless sensor network. Int. J. Grid Distrib. Comput. 7, 251–272 (2014)
Keshri, N., Mishra, B.K.: Two time-delay dynamic model on the transmission of malicious signals in wireless sensor network. Chaos Solitons Fractals 68, 151–158 (2014)
Li, Q., Zhang, B., Cui, L., Fan, Z., Athanasios, V.V.: Epidemics on small worlds of tree-based wireless sensor networks. J. Syst. Sci. Complex 27(6), 1095–1120 (2014)
O’Mahony, G.D., Harris, P.J., Murphy, C.C.: Analyzing the vulnerability of wireless sensor networks to a malicious matched protocol attack. In: 2018 International Carnahan Conference on Security Technology (ICCST), pp. 1–5. IEEE (2018)
Project Mesa Team: Mesa: Agent-Based Modeling in Python 3+ (2018). https://github.com/projectmesa/mesa/
Razak, M.F.A., Anuar, N.B., Salleh, R., Firdaus, A.: The rise of “malware”: bibliometric analysis of malware study. J. Netw. Comput. Appl. 75, 58–76 (2016)
del Rey, A.M., Guillén, J.H., Sánchez, G.R.: Modeling malware propagation in wireless sensor networks with individual-based models. In: Conference of the Spanish Association for Artificial Intelligence, pp. 194–203. Springer (2016)
Shen, S., Huang, L., Liu, J., Champion, A.C., Yu, S., Cao, Q.: Reliability evaluation for clustered WSNs under malware propagation. Sensors 16(6), 855 (2016)
Shen, S., Ma, H., Fan, E., Hu, K., Yu, S., Liu, J., Cao, Q.: A non-cooperative non-zero-sum game-based dependability assessment of heterogeneous wsns with malware diffusion. J. Netw. Comput. Appl. 91, 26–35 (2017)
Siegfried, R.: Modeling and Simulation of Complex Systems: A Framework for Efficient Agent-Based Modeling and Simulation. Springer, Berlin (2014)
Wang, T., Wu, Q., Wen, S., Cai, Y., Tian, H., Chen, Y., Wang, B.: Propagation modeling and defending of a mobile sensor worm in wireless sensor and actuator networks. Sensors 17(1), 139 (2017)
Wang, Y., Li, D., Dong, N.: Cellular automata malware propagation model for WSN based on multi-player evolutionary game. IET Netw. 7(3), 129–135 (2017)
Wurzer, G., Kowarik, K., Reschreiter, H.: Agent-based Modeling and Aimulation in Archaeology. Springer, Cham (2015)
Zhang, Z., Si, F.: Dynamics of a delayed SEIRS-V model on the transmission of worms in a wireless sensor network. Adv. Differ. Equations 2014(1), 295 (2014)
Zhu, L., Zhao, H.: Dynamical analysis and optimal control for a malware propagation model in an information network. Neurocomputing 149, 1370–1386 (2015)
Zhu, L., Zhao, H., Wang, X.: Stability and bifurcation analysis in a delayed reaction-diffusion malware propagation model. Comput. Math. Appl. 69(8), 852–875 (2015)
Acknowledgements
This research has been partially supported by Ministerio de Ciencia, Innovación y Universidades (MCIU, Spain), Agenda Estatal de Investigación (AEI, Spain), and Fondo Europeo de Desarrollo Regional (FEDER, UE) under project with reference TIN2017-84844-C2-2-R (MAGERAN) and the project with reference SA054G18 supported by Consejería de Educación (Junta de Castilla y León, Spain).
F.K. Batista has supported by IFARHU-SENACYT scholarship program (Panama).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Batista, F.K., del Rey, A.M., Queiruga-Dios, A. (2020). A Review of SEIR-D Agent-Based Model. In: Herrera-Viedma, E., Vale, Z., Nielsen, P., Martin Del Rey, A., Casado Vara , R. (eds) Distributed Computing and Artificial Intelligence, 16th International Conference, Special Sessions. DCAI 2019. Advances in Intelligent Systems and Computing, vol 1004. Springer, Cham. https://doi.org/10.1007/978-3-030-23946-6_15
Download citation
DOI: https://doi.org/10.1007/978-3-030-23946-6_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-23945-9
Online ISBN: 978-3-030-23946-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)