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SGuard: machine learning-based Distrbuted Denial-of-Service Detection Scheme for Software Defined Network

• 2021
العودة
معلومات البحث
المؤلفون Shimaa Ezzat Kotb, Heba .A Tag El-Dien, Adly S.Tag Eldien
الكلمات المفتاحية Software Defined Networking (SDN), SGuard, Distributed Denial o f Service attack (DDoS attack), Support Vector Machine (SVM).
المجلة العلمية Not Available
الناشر Not Available
المجلد Not Available
العدد Not Available
الصفحات Not Available
publication.type International
رابط البحث Not Available
المواد المرفقة Not Available
الملخص
A Software Defined Networking (SDN) is an
advanced network design that presents central control for a
complete network. It is a dynamic, easy-to-manage, costefficient, and adaptive advanced architecture, making it
utilitarian for dynamic nature and high-bandwidth of the
present applications. Distributed Denial-of-Service (DDoS)
attacks specific to SDN networks to deplete the control plane
bandwidth and overload the buffer memory of OpenFlow
switch.
In this research, a design and implementation of secure
guard to assist in solving the issue of DDoS attacks on pox
controller is presented, this guard is named SGuard. A novel
Five-tuple as feature vector is utilized for classifying traffic
flow using Support Vector Machine (SVM). A Mininet is
utilized to evaluate SGuard in a software environment. The
introduced system is evaluated by measuring the system’s
performance in terms of delay, bandwidth, traffic flow and
accuracy