DDoS Attack Preventing and Detection with the Artificial Intelligence Approach-Reference-Cited by-同舟云学术

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DDoS Attack Preventing and Detection with the Artificial Intelligence Approach

Published:2022 Issue: Volume: Page:30-43
ISSN:1865-0929
Container-title:Intelligent Computing Systems
language:
Short-container-title:

Author:

Islam Tariqul,Jabiullah Md. Ismail,Abid Dm. Mehedi Hasan

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-98457-1_3

Reference32 articles.

1. Yuan, X., Li, C., Li, X.: DeepDefense: identifying DDoS attack via deep learning. In: 2017 IEEE International Conference on Smart Computing (SMARTCOMP), Hong Kong, 2017, pp. 1–8 (2017). https://doi.org/10.1109/SMARTCOMP.2017.7946998

2. Guri, M., Mirsky, Y., Elovici,Y.: 9-1-1 DDoS: attacks, analysis and mitigation. In: 2017 IEEE European Symposium on Security and Privacy (EuroS&P), Paris, France, 2017, pp. 218–232 (2017). https://doi.org/10.1109/EuroSP.2017.23

3. Hsieh, C.J., Chan, T.Y.: Detection DDoS attacks based on neural-network using Apache Spark. In: 2016 International Conference on Applied System Innovation (ICASI), Okinawa, 2016, pp. 1–4 (2016). https://doi.org/10.1109/ICASI.2016.7539833

4. Kiruthika Devi, B.S., Preetha, G., Selvaram, G., Mercy Shalinie, S.: An impact analysis: real time DDoS attack detection and mitigation using machine learning. In: 2014 International Conference on Recent Trends in Information Technology, Chennai, 2014, pp. 1–7 (2014). https://doi.org/10.1109/ICRTIT.2014.6996133

5. Meitei, I.L., Singh, K.J., De, T.: Detection of DDoS DNS amplification attack using classification algorithm. In: Proceedings of the International Conference on Informatics and Analytics (ICIA-16), Article 81, p. 6. ACM, New York, NY, The USA (2016). https://doi.org/10.1145/2980258.2980431

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1. Comparative Study for Identifying and Categorizing DDoS Attacks;2024 21st Learning and Technology Conference (L&T);2024-01-15

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