Evaluating Machine Learning Algorithms for Detecting DDoS Attacks-Reference-Cited by-同舟云学术

Evaluating Machine Learning Algorithms for Detecting DDoS Attacks

Published:2011 Issue: Volume: Page:441-452
ISSN:1865-0929
Container-title:Advances in Network Security and Applications
language:
Short-container-title:

Author:

Suresh Manjula,Anitha R.

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-22540-6_42

Reference24 articles.

1. Anitha, N.: An Investigation into the detection and Mitigation of Denial of Service (DoS) Attacks, Monograph. Springer, Heidelberg (in press, 2011)

2. A Tutorial on Clustering Algorithms, http://Clustering-FuzzyC-means.htm

3. Lecture Notes in Computer Science;J. Cheng,2009

4. Erskin, E., Arnold, A., Prerau, M., Portnoy, L.: A Geometric Framework for Unsupervised Anomaly Detection: Detecting Intrusions in Unlabeled Data. In: Barbará, D., Jajodia, S. (eds.) Applications of Data Mining in Computer Security, pp. 77–102. Kluwer, Dordrecht (2002)

5. Jin, S., Yeung, D.S.: A covariance analysis model for ddos attack detection. In: Proceedings of IEEE International Conference on Communications, June 20-24, vol. 4, pp. 1882–1886. IEEE, Los Alamitos (2004)

Cited by 39 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An Investigation into the Performances of the State-of-the-art Machine Learning Approaches for Various Cyber-attack Detection: A Survey;2024 IEEE International Conference on Electro Information Technology (eIT);2024-05-30

2. Graph Convolutional Networks for DDoS Attack Detection in a Lossy Network;2024 IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN);2024-05-05

3. Ensembling Supervised and Unsupervised Machine Learning Algorithms for Detecting Distributed Denial of Service Attacks;Algorithms;2024-02-24

4. Trusting Classifiers with Interpretable Machine Learning Based Feature Selection Backpropagation;2024 IEEE 14th Annual Computing and Communication Workshop and Conference (CCWC);2024-01-08

5. Application of Large Language Models to DDoS Attack Detection;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2024