Comprehensive Survey of Machine Learning Techniques for Detecting and Preventing Network Layer DoS Attacks
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-45882-8_23
Reference20 articles.
1. Tayyab, M., Belaton, B., Anbar, M.: ICMPv6-based DoS and DDoS attacks detection using machine learning techniques, open challenges, and blockchain applicability: a review. IEEE Access 8, 170529–170547 (2020)
2. Xing, F., Wenye, W.: Understanding dynamic denial of service attacks in mobile ad hoc networks. In: MILCoM 2006–2006 IEEE Military Communications conference. IEEE (2006)
3. Verma, A., Saha, R., Kumar, N., Kumar, G., et al.: A detailed survey of denial of service for IoT and multimedia systems: past, present and futuristic development. Multimedia Tools Appl. 81(14), 19879–19944 (2022). https://doi.org/10.1007/s11042-021-11859-z
4. Gebremariam, G.G., Panda, J., Indu, S.: Blockchain-based secure localization against malicious nodes in IoT-based wireless sensor networks using federated learning. Wireless Commun. Mobile Comput. 2023 (2023)
5. Kukreti, S., et al.: DDoS attack using SYN flooding: a case study. In: 2022 9th International Conference on Computing for Sustainable Global Development (INDIACom). IEEE (2022)
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