Abstract
The paper analyzes possible types of attacks in the areas of information security of cyber-physical systems and surveys available literature in the field. We address a problem of the vulnerability of Internet of Things devices in wireless networks, assuming attacks aimed at depleting energy resources. In the paper we regarded several types of traffic and conducted an analysis of normal and attacking traffic. An approach to detection of energy depletion attacks in cyber-physical systems based on machine learning methods is proposed. The feasibility of the proposed solution is confirmed by an example of the attacking traffic by using the Python language and Anaconda pack.
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The work was financially supported by the Russian Foundation of Basic Research, project No. 19-07-00953.
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Balueva, A., Desnitsky, V., Ushakov, I. (2020). Approach to Detection of Denial-of-Sleep Attacks in Wireless Sensor Networks on the Base of Machine Learning. In: Kotenko, I., Badica, C., Desnitsky, V., El Baz, D., Ivanovic, M. (eds) Intelligent Distributed Computing XIII. IDC 2019. Studies in Computational Intelligence, vol 868. Springer, Cham. https://doi.org/10.1007/978-3-030-32258-8_41
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DOI: https://doi.org/10.1007/978-3-030-32258-8_41
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