Performance Comparison of Machine Learning and Deep Learning Models in DDoS Attack Detection-Reference-Cited by-同舟云学术

Performance Comparison of Machine Learning and Deep Learning Models in DDoS Attack Detection

Published:2023 Issue: Volume: Page:529-541
ISSN:1876-1100
Container-title:Lecture Notes in Electrical Engineering
language:
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Author:

Siddarkar Poonam^ORCID,Goudar R. H.^ORCID,Hukkeri Geeta S.^ORCID,Deshpande S. L.^ORCID,Kaliwal Rohit B.^ORCID,Patil Pooja S.^ORCID,Janagond Prashant^ORCID

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-99-5974-7_43

Reference25 articles.

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3. Yungaicela-Naula NM, Vargas-Rosales C, Perez-Diaz JA (2021) SDN-based architecture for transport and application layer DDoS attack detection by using machine and deep learning, vol 9. IEEE, pp 108495–108512

4. Horsanal E, Yigit Y, Secinti G, Karameseoglu A, Canberk B (2021) Network-Aware AutoML Framework for Software-Defined Sensor Networks. In: 17th international conference on distributed computing in sensor systems (DCOSS). IEEE, pp 451–457

5. Sridevi S, Prabha R, Reddy KN, Monic KM, Senthil GA, Razmah M (2022) Network intrusion detection system using supervised learning based voting classifier. In: International Conference on Communication, Computing, and Internet of Things (IC3IoT). IEEE, pp 1–6