Identifying DDoS attacks in 4G networks using artificial neural networks and principal component analysis Online publication date: Thu, 23-Sep-2021
by A.G. Nagesha; G. Mahesh; Gowrishankar
International Journal of Networking and Virtual Organisations (IJNVO), Vol. 25, No. 1, 2021
Abstract: Denial-of-service (DoS) attack is one in which attackers make certain queries by sending messages to the remote or target servers with an intention to stop or shutdown the servers. Those messages cause such an impact to the servers that it makes no response for the users. When this DoS attack is performed using number of systems that are compromised for attacking a single system, then it is called as distributed denial-of-service (DDoS) attack. In this paper, an artificial neural network (ANN) combined with principal component analysis (PCA) is used to identify the traffic as normal or a DDoS attack in 4G networks. The feature space dimension is reduced using PCA and the dimensionally reduced features are given as input to the feed forward neural network for training. The experiment is conducted using KDD dataset. The recognition accuracy of the proposed system is improved when compared to the existing systems using RBF networks, naive Bayes and random forest.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Networking and Virtual Organisations (IJNVO):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook