Machine learning method in detecting a distributed of service (DDoS): A systematic literature review
Author:
Publisher
AIP Publishing
Link
http://aip.scitation.org/doi/pdf/10.1063/5.0112715
Reference17 articles.
1. Rios, V. D. M., Inácio, P. R. M., Magoni, D., Freire, M., Rios, V. D. M., Inácio, P. R. M., Magoni, D., Freire, M., Miranda, V. De, Inácio, P. R. M., Magoni, D., & Freire, M. M. (2021). Detection of reduction-of-quality DDoS attacks using Fuzzy Logic and machine learning algorithms To cite this version : HAL Id : hal-03182934 Detection of Reduction-of-Quality DDoS Attacks Using Fuzzy Logic and Machine Learning Algorithms*.
2. T-CAD: A threshold based collaborative DDoS attack detection in multiple autonomous systems
3. Alsirhani, A., Sampalli, S., & Bodorik, P. (2019). DDoS Detection System : Using a Set of Classification Algorithms Controlled by Fuzzy Logic System in Apache Spark. 16(3), 936–949.
4. Ray, T. (2020). DDoS defence: new tactics for a rising shadow industry. Network Security, (4), 6–7.
5. He, Z., & Lee, R. B. (2017). Machine Learning Based DDoS Attack Detection From Source Side in Cloud. In 2017 IEEE 4th International Conference on Cyber Security and Cloud Computing (CSCloud), 114–120.
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