Future of Information and Communication Conference (FICC) 2024
4-5 April 2024
Publication Links
IJACSA
Special Issues
Future of Information and Communication Conference (FICC)
Computing Conference
Intelligent Systems Conference (IntelliSys)
Future Technologies Conference (FTC)
International Journal of Advanced Computer Science and Applications(ijacsa), Volume 7 Issue 1, 2016.
Abstract: Users and organizations find it continuously challenging to deal with distributed denial of service (DDoS) attacks. . The security engineer works to keep a service available at all times by dealing with intruder attacks. The intrusion-detection system (IDS) is one of the solutions to detecting and classifying any anomalous behavior. The IDS system should always be updated with the latest intruder attack deterrents to preserve the confidentiality, integrity and availability of the service. In this paper, a new dataset is collected because there were no common data sets that contain modern DDoS attacks in different network layers, such as (SIDDoS, HTTP Flood). This work incorporates three well-known classification techniques: Multilayer Perceptron (MLP), Naïve Bayes and Random Forest. The experimental results show that MLP achieved the highest accuracy rate (98.63%).
Mouhammd Alkasassbeh, Ghazi Al-Naymat, Ahmad B.A Hassanat and Mohammad Almseidin, “Detecting Distributed Denial of Service Attacks Using Data Mining Techniques” International Journal of Advanced Computer Science and Applications(ijacsa), 7(1), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070159
@article{Alkasassbeh2016,
title = {Detecting Distributed Denial of Service Attacks Using Data Mining Techniques},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070159},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070159},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {1},
author = {Mouhammd Alkasassbeh and Ghazi Al-Naymat and Ahmad B.A Hassanat and Mohammad Almseidin}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.