| Title | Automated DDoS Attack Mitigation for Software Defined Network |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Wang, Danni, Li, Sizhao |
| Conference Name | 2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID) |
| Keywords | composability, control systems, DDoS Attack, DDoS attack mitigation, ddos mitigation, denial-of-service attack, feature extraction, Human Behavior, k-nearest neighbor, Metrics, network architecture, Network security, pubcrawl, Real-time Systems, resilience, Resiliency, Software Defined Network, Switches |
| Abstract | Network security is a prominent topic that is gaining international attention. Distributed Denial of Service (DDoS) attack is often regarded as one of the most serious threats to network security. Software Defined Network (SDN) decouples the control plane from the data plane, which can meet various network requirements. But SDN can also become the object of DDoS attacks. This paper proposes an automated DDoS attack mitigation method that is based on the programmability of the Ryu controller and the features of the OpenFlow switch flow tables. The Mininet platform is used to simulate the whole process, from SDN traffic generation to using a K-Nearest Neighbor model for traffic classification, as well as identifying and mitigating DDoS attack. The packet counts of the victim's malicious traffic input port are significantly lower after the mitigation method is implemented than before the mitigation operation. The purpose of mitigating DDoS attack is successfully achieved. |
| Notes | ISSN: 2163-5056 |
| DOI | 10.1109/ASID56930.2022.9996013 |
| Citation Key | wang_automated_2022 |
Automated DDoS Attack Mitigation for Software Defined Network