Machine learning-based anomaly detection in NFV: a comprehensive survey

Sehar Zehra and Ummay Faseeha and Hassan Jamil Syed and Fahad Samad and Ashraf Osman Ibrahim Elsayed and Anas W. Abulfaraj and Wamda Nagmeldin (2023) Machine learning-based anomaly detection in NFV: a comprehensive survey. Sensors, 23. pp. 1-26. ISSN 1996-2022

	Text ABSTRACT.pdf Download (37kB)
	Text FULL TEXT.pdf Restricted to Registered users only Download (761kB) | Request a copy

Abstract

Network function virtualization (NFV) is a rapidly growing technology that enables the virtualization of traditional network hardware components, offering benefits such as cost reduction, increased flexibility, and efficient resource utilization. Moreover, NFV plays a crucial role in sensor and IoT networks by ensuring optimal resource usage and effective network management. However, adopting NFV in these networks also brings security challenges that must promptly and effectively address. This survey paper focuses on exploring the security challenges associated with NFV. It proposes the utilization of anomaly detection techniques as a means to mitigate the potential risks of cyber attacks. The research evaluates the strengths and weaknesses of various machine learningbased algorithms for detecting network-based anomalies in NFV networks. By providing insights into the most efficient algorithm for timely and effective anomaly detection in NFV networks, this study aims to assist network administrators and security professionals in enhancing the security of NFV deployments, thus safeguarding the integrity and performance of sensors and IoT systems.

Item Type:	Article
Keyword:	network function virtualization (NFV); Internet of Things (IoT); security challenges; anomaly detection; cyber-attacks; machine learning based; supervised learning; unsupervised learning
Subjects:	Q Science > Q Science (General) > Q1-390 Science (General) > Q300-390 Cybernetics T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1-9971 Electrical engineering. Electronics. Nuclear engineering > TK5101-6720 Telecommunication Including telegraphy, telephone, radio, radar, television
Department:	FACULTY > Faculty of Computing and Informatics
Depositing User:	ABDULLAH BIN SABUDIN -
Date Deposited:	09 Feb 2024 11:13
Last Modified:	09 Feb 2024 11:13
URI:	https://eprints.ums.edu.my/id/eprint/38205

Actions (login required)

View Item