Abstract
The Internet of Things (IoT) is filling cities and buildings. It provides continuous monitoring and control to the point where a large proportion of everyday processes can be automated. This is possible because of the large number of devices that are available. However, one of the main challenges is securing all these devices due to the proliferation of malware aimed at manipulating data or even creating botnets attacking other sensor networks. In this paper, regardless of the network topology or even the type of malware sample infecting the sensor network, we propose a new algorithm capable of removing infected nodes from sensor networks. Two simulations on two networks with different topologies were performed to validate the algorithm.
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Severt, M., Casado-Vara, R., del Rey, A.M., Jove, E., Quintián, H., Calvo-Rolle, J.L. (2023). Finding and Removing Infected T-Trees in IoT Networks. In: García Bringas, P., et al. International Joint Conference 16th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2023) 14th International Conference on EUropean Transnational Education (ICEUTE 2023). CISIS ICEUTE 2023 2023. Lecture Notes in Networks and Systems, vol 748. Springer, Cham. https://doi.org/10.1007/978-3-031-42519-6_14
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DOI: https://doi.org/10.1007/978-3-031-42519-6_14
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