| Title | DDoS Attack Detection and Mitigation at SDN Data Plane Layer |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Abdulkarem, H. S., Dawod, A. |
| Conference Name | 2020 2nd Global Power, Energy and Communication Conference (GPECOM) |
| Date Published | Oct. 2020 |
| Publisher | IEEE |
| ISBN Number | 978-1-7281-6264-5 |
| Keywords | Automated Secure Software Engineering, centralized control point, composability, computer network security, control plane, DDoS Attack, DDoS attack detection, DDoS attack mitigation, denial-of-service attack, distributed denial-of-service attack, forwarding plane, Human Behavior, malicious traffic abnormal behavior, Metrics, network functions, network infrastructure, normal traffic, open daylight controller, Open vSwitch programmability feature, Opendaylight, OpenFlow, Programming, pubcrawl, python, quality of service, resilience, Resiliency, SDN, SDN data plane layer, SDN data-plane, SDN environment, SDN specifications, Servers, Software, software defined networking, software-defined networking, Switches, telecommunication traffic, time 100.0 s to 150.0 s, virtualisation, written SDN application |
| Abstract | In the coming future, Software-defined networking (SDN) will become a technology more responsive, fully automated, and highly secure. SDN is a way to manage networks by separate the control plane from the forwarding plane, by using software to manage network functions through a centralized control point. A distributed denial-of-service (DDoS) attack is the most popular malicious attempt to disrupt normal traffic of a targeted server, service, or network. The problem of the paper is the DDoS attack inside the SDN environment and how could use SDN specifications through the advantage of Open vSwitch programmability feature to stop the attack. This paper presents DDoS attack detection and mitigation in the SDN data-plane by applying a written SDN application in python language, based on the malicious traffic abnormal behavior to reduce the interference with normal traffic. The evaluation results reveal detection and mitigation time between 100 to 150 sec. The work also sheds light on the programming relevance with the open daylight controller over an abstracted view of the network infrastructure. |
| URL | https://ieeexplore.ieee.org/document/9247850 |
| DOI | 10.1109/GPECOM49333.2020.9247850 |
| Citation Key | abdulkarem_ddos_2020 |
DDoS Attack Detection and Mitigation at SDN Data Plane Layer