Multi-Layer Ensemble Deep Reinforcement Learning based DDoS Attack Detection and Mitigation in Cloud-SDN Environment

Title

Multi-Layer Ensemble Deep Reinforcement Learning based DDoS Attack Detection and Mitigation in Cloud-SDN Environment

Creator

Christila S.A.; Sivakumar R.

Description

Cloud computing (CC) remains as a promising environment which offers scalable and cost effectual computing facilities. The combination of the SDN technique with the CC platform simplifies the complexities of cloud networking and considerably enhances the scalability, manageability, programmability, and dynamism of the cloud. This study introduces a novel Multi-Layer Ensemble Deep Reinforcement Learning based DDoS Attack Detection and Mitigation (MEDR-DDoSAD) technique in Cloud-SDN Environment. The major aim of the presented technique lies in the recognition of DDoS attacks from the cloud-SDN platform. The MEDR-DDoSAD technique transforms the input data into images and the features are derived via deep convolutional neural network based Xception model. 2022 IEEE.

Source

4th International Conference on Circuits, Control, Communication and Computing, I4C 2022, pp. 451-455.

Date

2022-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Cloud environment; DDoS attacks; Deep learning; Reinforcement learning; Software defined network

Coverage

Christila S.A., CHRIST (Deemed to Be University), Dept. of Computer Science, Karnataka, Bengaluru, India; Sivakumar R., CHRIST (Deemed to Be University), Dept. of Computer Science, Karnataka, Bengaluru, India

Rights

Restricted Access

Relation

ISBN: 979-835039747-5

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/I4C57141.2022.10057641

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150244806&doi=10.1109%2fI4C57141.2022.10057641&partnerID=40&md5=04f16986941ff2e850718bad897f5402