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Assessment of a Semi-supervised Machine Learning Method for Thwarting Network DDoS Assaults

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Evolution in Signal Processing and Telecommunication Networks (ICMEET 2023)

Abstract

In latest existence, Path identifiers (PID) have utilised as inter-domain routing (IDR) things in association. Though, the PIDs utilised in present methods are immobile that creates it simple for attacker to introduce D DoS flooding attacks. To discourse this problem, current a D-PID structure, which make use of PIDs negotiated among neighbouring domains as IDR substance. The PID of the inter-domain connection between two domains in DPID is going to be kept private and can vary periodically. Cryptographic techniques may be employed as well to safeguard the security of information shared over a network. There is a good possibility that DPID’s data-secure technique will stop networking D DoS assaults.

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Correspondence to E. Laxmi Lydia .

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Lakshmi, S.G., Durga, T.N.V., Srilatha, P., Kumari, C.H.D.V.P., Laxmi Lydia, E., Akhmetshin, E. (2024). Assessment of a Semi-supervised Machine Learning Method for Thwarting Network DDoS Assaults. In: Bhateja, V., Chowdary, P.S.R., Flores-Fuentes, W., Urooj, S., Sankar Dhar, R. (eds) Evolution in Signal Processing and Telecommunication Networks. ICMEET 2023. Lecture Notes in Electrical Engineering, vol 1155. Springer, Singapore. https://doi.org/10.1007/978-981-97-0644-0_28

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  • DOI: https://doi.org/10.1007/978-981-97-0644-0_28

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  • Print ISBN: 978-981-97-0643-3

  • Online ISBN: 978-981-97-0644-0

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