A Survey on DDoS Attack Detection Methods Employing Intelligent Techniques |
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| © 2020 by IJCTT Journal | ||
| Volume-68 Issue-11 |
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| Year of Publication : 2020 | ||
| Authors : Vinayak P R, Gripsy Paul | ||
| DOI : 10.14445/22312803/IJCTT-V68I11P113 | ||
How to Cite?
Vinayak P R, Gripsy Paul, "A Survey on DDoS Attack Detection Methods Employing Intelligent Techniques," International Journal of Computer Trends and Technology, vol. 68, no. 11, pp. 83-85, 2020. Crossref, 10.14445/22312803/IJCTT-V68I11P113
Abstract
The Distributed denial-of-service (DDOS) attacks target network resources to disable the websites or services through overloading the resources with a large amount of traffic. The arrival of intelligent systems such as machine learning-based techniques and deep learning techniques have improved the automatic detection of such attacks. The machine-learning-based techniques such as support vector machine (SVM), decision tree, or Na¨?ve Bayes (NB) can efficiently use for classification. CNN or other techniques can also use for constructing deep neural networks to detect attacks. In this paper, we discuss in detail various DDoS attack detection methods.
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Keywords
attack detection, DDoS, deep learning, machine learning, network security