Abstract
Usually statistical techniques are employed to analyze malware behavior mainly through machine learning-based methods. However it seems legitimate to wonder if some statistical methods could be useful as a complementary tool to malicious code propagation models. This work explores this possibility with a first (and simple) application of the use of survival analysis to the study of the simulations obtained from a compartmental and individual SI model whose dynamics is described by means of a cellular automaton. The results obtained are in line with what could reasonably be expected.
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Acknowledgement
This work has been supported by Fundación Memoria D. Samuel Solórzano Barruso (Universidad de Salamanca, Spain) under research grant FS/2-2022.
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Frutos-Bernal, E., Martín del Rey, A., Rodríguez-Rosa, M. (2023). On the Statistical Analysis of an Individual-Based SI Model for Malware Propagation on WSNs. 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_18
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