Machine Learning Techniques for Detecting DDoS Attacks in SDN
Author:
Affiliation:
1. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology,Department of CSE,Chennai,India
2. Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Chennai,Department of ECE,Chennai,Tamil Nadu,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10028980/10028739/10029110.pdf?arnumber=10029110
Reference15 articles.
1. A survey of network-based intrusion detection data sets
2. LSTM-BA: DDoS Detection Approach Combining LSTM and Bayes
3. Review of intrusion detection systems based on deep learning techniques: coherent taxonomy, challenges, motivations, recommendations, substantial analysis and future directions
4. Machine learning approaches to IoT security: A systematic literature review
5. Novel Cluster Rotating and Routing Strategy for software defined Wireless Sensor Networks
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1. Beyond Traditional Boundaries: A Survey of Security Mechanisms in Software-Defined Networks;2024 Second International Conference on Emerging Trends in Information Technology and Engineering (ICETITE);2024-02-22
2. Machine Learning and Deep Learning Techniques for Distributed Denial of Service Anomaly Detection in Software Defined Networks—Current Research Solutions;IEEE Access;2024
3. Application-Layer DDoS Detection via Efficient Machine Learning and Feature Selection;2023 International Conference on Engineering Applied and Nano Sciences (ICEANS);2023-10-25
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