Találati lista | Tudóstér

001-es BibID:	BIBFORM117946
035-os BibID:	(WOS)000565865300009
Első szerző:	Nsaif, Mohammed (informatics)
Cím:	Detection and Prevention Algorithm of DDoS Attack Over the IOT Networks / Mohammed Ridha Nsaif, Mohammed Falah Abbood, Abbas Fadhil Mahdi
Dátum:	2020
ISSN:	2217-8309 2217-8333
Megjegyzések:	Traffic classification is a crucial aspect for Software- Defined Networking functionalities. This paper is a part of an on-going project aiming at optimizing power consumption in the environment of software-defined datacenter networks. We have developed a novel routing strategy that can blindly balance between the power consumption and the quality of service for the incoming traffic flows. In this paper, we demonstrate how to classify the network traffic flows so that the quality of service of each flow-class can be guaranteed efficiently. This is achieved by creating a dataset that encompasses different types of network traffic such as video, VoIP, game and ICMP. The performance of a number of Machine Learning techniques is compared and the results are reported. As part of future work, we will incorporate classification into the power consumption model towards achieving further advances in this research area.
Tárgyszavak:	Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk Machine learning classification dataset SDN
Megjelenés:	TEM Journal-Technology Education Management Informatics. - 9 : 3 (2020), p. 899-906. -
További szerzők:	Mohammed, Falah Abbood Abbas Fadhil Mahdi
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
Borító:
Saját polcon: