A Flow-Based Anomaly Detection Approach With Feature Selection Method Against DDoS Attacks in SDNs
Author:
Affiliation:
1. School of Computer Science, University College Dublin, Dublin, Ireland
2. National Telecommunication Institute, Nile University, Cairo, Egypt
Funder
The Research Funding is University Collage Dublin
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Artificial Intelligence,Computer Networks and Communications,Hardware and Architecture
Link
http://xplorestaging.ieee.org/ielx7/6687307/9976263/09810168.pdf?arnumber=9810168
Reference65 articles.
1. DDoS Attack Detection Method Based on Improved KNN With the Degree of DDoS Attack in Software-Defined Networks
2. Network Anomaly Detection Using LSTM Based Autoencoder
3. A cooperative DDoS attack detection scheme based on entropy and ensemble learning in SDN
4. JESS: Joint Entropy-Based DDoS Defense Scheme in SDN
5. SAFETY: Early Detection and Mitigation of TCP SYN Flood Utilizing Entropy in SDN
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