Abstract
Denial of Service (DoS) attack over Internet of Things (IoT) is among the most prevalent cyber threat, their complex behavior makes very expensive the use of Datagram Transport Layer Security (DTLS) for securing purposes. DoS attack exploits specific protocol features, causing disruptions and remaining undetected by legitimate components. This paper introduces a set of one-class reconstruction methods such as auto-encoder, K-Means and PCA (Principal Component Analysis) for developing a categorization model in order to prevent IoT DoS attacks over the CoAP (Constrained Application Protocol) environments.
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Acknowledgments
Álvaro Michelena’s research was supported by the Spanish Ministry of Universities (https://www.universidades.gob.es/), under the “Formación de Profesorado Universitario” grant with reference FPU21/00932.
Míriam Timiraos’s research was supported by the Xunta de Galicia (Regional Government of Galicia) through grants to industrial Ph.D. (http://gain.xunta.gal), under the Doutoramento Industrial 2022 grant with reference: \(04_IN606D_2022_2692965\). CITIC, as a Research Center of the University System of Galicia, is funded by Consellería de Educación, Universidade e Formación Profesional of the Xunta de Galicia through the European Regional Development Fund (ERDF) and the Secretaría Xeral de Universidades (Ref. ED431G 2019/01).
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Michelena, Á. et al. (2023). One-Class Reconstruction Methods for Categorizing DoS Attacks on CoAP. In: García Bringas, P., et al. Hybrid Artificial Intelligent Systems. HAIS 2023. Lecture Notes in Computer Science(), vol 14001. Springer, Cham. https://doi.org/10.1007/978-3-031-40725-3_1
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DOI: https://doi.org/10.1007/978-3-031-40725-3_1
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