Volume 11 - Volume 11
Detecting Ddos Attack Using Adaptive Boosting with Software Defined Network in Cloud Computing Environment
Abstract
Cloud computing is most widely used platform in past decade for computational operations in the
computers and which offers the cost effective system with the measurable results. Cloud computing and
software defined network (SDN) combination gives the better environment which reduces the
difficulties with the cloud network and improves the dynamism, programmability, scalability and
manageability of the cloud. Several weaknesses are attacked on one side by changing the SDN pattern
into the centralized architecture namely as Distribute denial of service (DDoS) attacks. So these
interrupts are detected and then prevented in SDN with the technology. Detecting of DDoS attack by
using anomaly-based adaptive boosting in SDN cloud environment is presented in this paper. By
coordinating the SDN features with the adaptive boosting algorithm, the cloud environment of SDN
system DDoS attacks are noticed and prevented. Decision stump is used to generate the learning data
and serves huge data to the servers within less time which is used as the prediction data. Predictions
are can be processed by the formation of learning data. The experimental test results show that the
adaptive boosting algorithm with SDN features has effectiveness in detecting attacks with high
accuracy and in the SDN the DDoS attacks are detected even in the low communication.
Paper Details
PaperID: 2387
Author's Name: Sisay Wayu Tufa, Mesay Mengstie, Haftom Gebregziabher and B. Ravindra Babu
Volume: Volume 11
Issues: Volume 11
Keywords: SDN, DDoS, Cloud Computing, Adaptive Boosting Algorithm, Attack Detection.
Year: 2021
Month: July
Pages: 3485-3494